Jernbaneverket Norwegian High Speed Railway Assessment …...Subject 1: Demand Forecasting Final Report 04/03/2011 (With additional information) Contract 5, Subject 1: Demand Forecasting

/Market Analysis Demand Forecasting Final

Report_UPDATED_040311.docx

Jernbaneverket Norwegian High Speed Railway Assessment Project Contract 5: Market Analysis Subject 1: Demand Forecasting Final Report 04/03/2011 (With additional information)

Contract 5, Subject 1: Demand Forecasting 2

5096833/Market Analysis Demand Forecasting Final Report_UPDATED_040311.docx

Notice

This document and its contents have been prepared and are intended solely for Jernbaneverket’s information and use in relation to The Norwegian High Speed Rail Assessment Project.

WS Atkins International Ltd assumes no responsibility to any other party in respect of or arising out of or in connection with this document and/or its contents.

Document History

JOB NUMBER: 5096833 DOCUMENT REF: Market Analysis Demand Forecasting

Final Report_UPDATED_040311.docx

Revision Purpose Description Originated Checked Reviewed Authorised Date

1 Skeleton of Final Report MH LMG JD MH 29/10/10

2 Interim Report TH/JM LMG MH WL 12/01/11

3 Draft Final Report TH/JM LMG MH WL 02/02/11

4 Final Report TH AB MH WL 18/02/11

5 Additional Information TH MH JD MH 04/03/11



Contract 5: Market Analysis

Subject: Demand Forecasting

Final Report



Table of contents

Executive Summary 10

1 Introduction 16

1.1 Background 16

1.2 Overall Context of the Market Analysis Contract 17

1.3 Purpose of Subject 1: Demand Potential for HSR in Norway 17

1.4 This Report 18

2 Current Travel Markets 19

2.1 Introduction 19

2.2 Size of Existing Travel Markets 19

2.3 Comparison of Services 40

2.4 International Benchmarking 52

2.5 Key Overall Conclusions 57

3 Future ‘Do Minimum’ Travel Market 58

3.1 Introduction 58

3.2 Overview of Future Year Forecasting Approach – NTM5 matrices 58

3.3 Future Year „Do Minimum‟ Demand Growth 62

3.4 Comparison of Medium Term Forecasts: NTM5 versus Transport Operators 70

3.5 Conclusions 72

4 HSR Demand and Revenue Forecasts 73

4.1 Introduction 73

4.2 Approach to demand and revenue forecasting 73

4.3 Traffic forecasts on national corridors 77

4.4 Oslo – Bergen corridor 78

4.5 Bergen/Stavanger – Oslo corridor (Haukeli route – Y shaped route) 89

4.6 Stavanger – Bergen corridor (Haugesund route) 94

4.7 Stavanger – Kristiansand – Oslo corridor 98

4.8 Trondheim – Oslo corridor 109

4.9 Oslo – Stockholm corridor 121

4.10 Oslo – Gothenburg corridor 130

5 Conclusions 136

5.1 Introduction 136

5.2 Summary of Current Travel Markets 136

5.3 Future (Do Minimum) Travel Market 136

5.4 Commentary on demand and revenue forecasts 137

5.5 Recommendations for Phase 3 141



List of Tables

Table 2.1 – Total annual demand for key corridors in Norway for main transport modes (2010) 23

Table 2.2 – Annual business demand for key corridors in Norway for main transport modes (2010) 26

Table 2.3 – Annual leisure demand for key corridors in Norway for main transport modes (2010) 27

Table 2.4 – Top ten ticketed tourist attractions in Norway (2007) 35

Table 2.5 – Top ten free tourist attractions in Norway (2006) 35

Table 2.6 – Summary of rail level of service in Trondheim corridor (2010) 41

Table 2.7 – Summary of rail level of service in Bergen corridor (2010) 41

Table 2.8 – Summary of rail level of service in Kristiansand-Stavanger corridor (2010) 42

Table 2.9 – Summary of rail level of service in Gothenburg corridor (2010) 42 Table 2.10 – Summary of rail level of service in Stockholm corridor (2010) 43

Table 2.11 – Summary of local rail services in Norway 43

Table 2.12 – Summary of coach level of service in Trondheim corridor (2010) 44

Table 2.13 – Summary of coach level of service in Bergen corridor (2010) 45

Table 2.14 – Summary of coach level of service in Kristiansand-Stavanger corridor (2010) 45

Table 2.15 – Summary of coach level of service in Bergen-Stavanger corridor (2010) 45

Table 2.16 – Summary of coach level of service in Gothenburg corridor (2010) 46 Table 2.17 – Summary of coach level of service in Stockholm corridor (2010) 46

Table 2.18 – Summary of ferry level of service in Bergen-Stavanger corridor (2010) 47

Table 2.19 – Summary of air level of service on key routes within Norway and to Sweden (2010) 47

Table 2.20 – Access to key airports in Norway and Sweden (2010) 48 Table 2.21 – Summary of 2010 service frequency on key corridors 49

Table 2.22 – Summary of 2010 fastest journey times on key corridors (hr:min) 49

Table 2.23 – Summary of 2010 range of fares on key corridors (NOK) 50

Table 2.24 – Size of HSR markets in other European countries (2008) 52

Table 2.25 – Market share of HSR and air on key routes in other European countries (2008) 53

Table 2.26 – Summary of level of service on HSR in Sweden (2010) 53

Table 2.27 – Summary of level of service on HSR in France (2010) 54

Table 2.28 – Summary of level of service on HSR in Germany (2010) 54

Table 2.29 – Summary of level of service on HSR in Spain (2010) 55

Table 2.30 – Summary of level of service on HSR in the UK (2010) 56

Table 3.1 – Population projections index – Statistics Norway (SSB) 59 Table 3.2 – NSB‟s future rail demand indices: 2009-2017 (selected years) 70

Table 3.3 – Comparison of medium-term rail demand growth rates 2010-2018 71

Table 3.4 – Comparison of medium-term air growth rates 2010-2018 71

Table 4.1 – Representation of Changes in Supply in NTM5B 74

Table 4.2 – HSR / Classic Corridor Level of Service by Scenario 76

Table 4.3 – Summary of HSR Routes and Scenarios tested 77

Table 4.4 – Corridor Demand by Mode and Purpose (Scenarios A and B1) 79

Table 4.5 – Rail demand by trip type and exogenous growth (Scenario A 2024 to 2043) 80 Table 4.6 – Impact of Scenario B1 (additional rail journeys over Do Minimum 2024, 2043) 81

Table 4.7 – Summary of HSR Demand and Revenue: Scenario C Oslo – Bergen (Hallingdal route via

Hønefoss, Gol and Voss) 2024 81 Table 4.8 – HSR Demand by Origin/Destination type: Scenario C Oslo – Bergen (Hallingdal route via

Hønefoss, Gol and Voss) 2024 82 Table 4.9 – Boardings by station Scenario C Oslo – Bergen (Hallingdal route via Hønefoss, Gol and Voss)

2024 82

Table 4.10 – Summary of HSR Demand and Revenue: Scenario D Oslo – Bergen (via Voss) 2024 85

Table 4.11 – HSR Demand by Origin/Destination type: Scenario D Oslo – Bergen (via Voss) 2024 85



Table 4.12 – Boardings by station: Scenario D Oslo – Bergen (via Voss) 2024 86

Table 4.13 – Summary of HSR Demand and Revenue: Scenario D Oslo – Bergen/Stavanger (Haukeli route

non-stop) 2024 89 Table 4.14 – HSR Demand by Origin/Destination type: Scenario D Oslo – Bergen/Stavanger (Haukeli route

non-stop) 2024 90

Table 4.15 – Boardings by station: Scenario D Oslo – Bergen/Stavanger (Haukeli route non-stop) 2024 90 Table 4.16 – Summary of HSR Demand and Revenue: Scenario D Stavanger – Bergen (via Haugesund)

2024 94 Table 4.17 – HSR Demand by Origin/Destination type: Scenario D Stavanger – Bergen (via Haugesund)

2024 95

Table 4.18 – Boardings by station: Scenario D Stavanger – Bergen (via Haugesund) 2024 95 Table 4.19 – Corridor Demand by Mode and Purpose (Scenarios A and B2) 99

Table 4.20 – Rail demand by trip type and exogenous growth (Scenario A 2024 to 2043) 100

Table 4.21 – Growth over Scenario A – Scenario B2 101 Table 4.22 – Summary of HSR Demand and Revenue: Scenario C Oslo –Stavanger (via Drammen,

Porsgrunn, Arendal, Kristiansand) 2024 101

Table 4.23 – HSR Demand by Origin/Destination type: Scenario C Oslo –Stavanger (via Drammen,

Porsgrunn, Arendal, Kristiansand) 2024 102

Table 4.24 – Boardings by station: Scenario C Oslo –Stavanger (via Drammen, Porsgrunn, Arendal,

Kristiansand) 2024 102

Table 4.25 – Summary of HSR Demand and Revenue: Scenario D Oslo – Stavanger (via Porsgrunn and


Table 4.26 – HSR Demand by Origin/Destination type: Scenario D Oslo – Stavanger (via Porsgrunn and


Table 4.27 – Boardings by station: Scenario D Oslo – Stavanger (via Porsgrunn and Kristiansand) 2024 106

Table 4.28 – Corridor Demand by Mode and Purpose (Scenarios A and B3) 110

Table 4.29 – Rail Demand by Sector (Scenarios A and B3) 111 Table 4.30 – Growth Over Scenario A – Scenario B3 112

Table 4.31 – Summary of HSR Demand and Revenue: Scenario C Oslo – Trondheim (via Gardermoen,

Hamar, Lillehammer and Otta) 2024 112 Table 4.32 – HSR Demand by Origin/Destination type: Scenario C Oslo – Trondheim (via Gardermoen,

Hamar, Lillehammer and Otta) 2024 113 Table 4.33 – Boardings by station: Scenario C Oslo – Trondheim (via Gardermoen, Hamar, Lillehammer and

Otta) 2024 113

Table 4.34 – Summary of HSR Demand and Revenue: Scenario D Oslo – Trondheim (via Gardermoen)

2024 116

Table 4.35 – HSR Demand by Origin/Destination type: Scenario D Oslo – Trondheim (via Gardermoen) 2024116 Table 4.36 – Boardings by station: Scenario D Oslo – Trondheim (via Gardermoen) 2024 117

Table 4.37 – Corridor Demand by Mode and Purpose 122

Table 4.38 – Rail Demand by Sector (Scenarios A and B5) 123

Table 4.39 – Growth over Scenario A – Scenario B5 124 Table 4.40 – Summary of HSR Demand and Revenue: Scenario C Oslo – Stockholm (via Lillestrøm and

Kongsvinger) 2024 124

Table 4.41 – HSR Demand by Origin/Destination type: Scenario D Oslo – Stockholm (via Lillestrøm and

Kongsvinger) 2024 125

Table 4.42 – Boardings by station: Scenario C Oslo – Stockholm (via Lillestrøm and Kongsvinger) 2024 125

Table 4.43 – Summary of HSR Demand and Revenue: Scenario D Oslo – Stockholm (via Lillestrøm) 2024127

Table 4.44 – HSR Demand by Origin/Destination type: Scenario D Oslo – Stockholm (via Lillestrøm) 2024127

Table 4.45 – Boardings by station: Scenario D Oslo – Stockholm (via Lillestrøm) 2024 127

Table 4.46 – Corridor Demand by Mode and Purpose (Scenarios A and B4) 131 Table 4.47 – Rail Demand by Sector 132



Table 4.48 – Growth Over Scenario A – Scenario B4 133

Table 4.49 – Summary of HSR Demand and Revenue: Scenario D Oslo – Gothenburg (non-stop) 2024 133

Table 4.50 – HSR Demand by Origin/Destination type: Scenario D Oslo – Gothenburg (non-stop) 2024 134

Table 4.51 – Boardings by station: Scenario D Oslo – Gothenburg (non-stop) 2024 134 Table 5.1 – HSR Demand per Day by Corridor for Each Scenario (2024) 139

Table 5.2 – HSR per Year by Corridor for Each Scenario (2024) 139

Table 5.3 – Average HSR Demand per Train by Corridor for Scenarios C and D (2024) 140

Table 5.4 – HSR Revenue per Year for Scenarios C and D (2024) 140

List of Figures

Figure 2.1 – Population density in Norway by municipality (2010) 21

Figure 2.2 – Average (median) net income in Norway by municipality (2008) 22

Figure 2.3 – City areas included in the calculation of demand for city-to-city travel 24

Figure 2.4 – Total demand for each mode by corridor 25

Figure 2.5 – Business demand for each mode by corridor (2010) 26

Figure 2.6 – Mode share for city-to-city business trips by corridor (2010) 27 Figure 2.7 – Leisure demand for each mode by corridor (2010) 28

Figure 2.8 – Mode share for city-to-city leisure trips by corridor (2010) 28

Figure 2.9 – Wider catchment areas for Norwegian airports for the calculation of road and rail demand 30

Figure 2.10 – Number of business trips by corridor and mode (2010) 31 Figure 2.11 – Mode share by corridor for business trips (2010) 32

Figure 2.12 – Number of leisure trips by corridor and mode (2010) 32

Figure 2.13 – Mode share by corridor for leisure trips (2010) 33

Figure 2.14 – Location of major ski resorts in Norway 34

Figure 2.15 – Location of major tourist attractions and fjords in Norway and international guest nights in 200936

Figure 2.16 – Location of major tourist attractions and fjords in Norway and domestic guest nights in 2009 37

Figure 2.17 – Proportion of international tourists by arrival mode (2009) 38 Figure 2.18 – Proportion of Swedish tourists by arrival mode (2009) 38

Figure 3.1 – Population growth profiles (2010-2060) 60

Figure 3.2 – Projected growth of business air travel to 2060 63

Figure 3.3 – Projected growth of leisure air travel to 2060 63 Figure 3.4 – Projected growth of business rail travel to 2060 64

Figure 3.5 – Projected growth of leisure rail travel to 2060 64

Figure 3.6 – Projected growth of business car travel to 2060 65

Figure 3.7 – Projected growth of leisure car travel to 2060 65

Figure 3.8 – Projected growth of business coach travel to 2060 66

Figure 3.9 – Projected growth of leisure coach travel to 2060 66

Figure 3.10 – Compound Annual Growth Rates (CAGR) – Business 2010-2060 67

Figure 3.11 – Absolute growth in annual journeys – Business 2010-2060 67 Figure 3.12 – Compound Annual Growth Rates (CAGR) – Leisure 2010-2060 68

Figure 3.13 – Absolute growth in annual journeys – Leisure 2010-2060 68

Figure 3.14 – Comparison between population growth and growth in business travel (2010=100) 69

Figure 3.15 – Comparison between population growth and leisure travel (2010=100) 69 Figure 3.16 – Medium-term rail demand growth by corridor: NSB vs. NTM5 70

Figure 4.1 – Scen A (2024) Bergen Daily Demand Profile 78

Figure 4.2 – Scen B (2024) Bergen Daily Demand Profile 79 Figure 4.3 – Mode Share: Scenario C Oslo – Bergen via Hønefoss, Gol and Voss 2024 (Oslo/Akershus-

Bergen) 83



Figure 4.4 – Highest abstraction of journeys: Scenario C Oslo – Bergen (Hallingdal route via Hønefoss, Gol

and Voss) 2024 83

Figure 4.5 – HSR demand by originating zone (annual) and point of boarding (daily) 84 Figure 4.6 – Mode Share: Scenario D Oslo – Bergen via Voss 2024 (Oslo/Akershus-Bergen) 86

Figure 4.7 – Highest abstraction of journeys: Scenario D Oslo – Bergen (via Voss) 2024 87

Figure 4.8 – HSR demand by originating zone (annual) and point of boarding (daily) 88

Figure 4.9 – Mode Share: Scenario D Oslo – Bergen non-stop 2024 (Oslo/Akershus-Bergen) 91 Figure 4.10 – Mode Share: Scenario D Oslo – Stavanger non-stop 2024 (Oslo/Akershus-Stavanger) 91

Figure 4.11 – Highest abstraction of journeys: Scenario D Oslo – Bergen/Stavanger (Haukeli route non-stop)

2024 92


Figure 4.13 – Mode Share: Scenario D Stavanger – Bergen via Haugesund 2024 (Stavanger-Bergen) 96

Figure 4.14 – Highest abstraction of journeys: Scenario D Stavanger – Bergen (via Haugesund) 2024 96


Figure 4.16 – Scen A (2024) Stavanger Daily Demand Profile 98

Figure 4.17 – Scen B (2024) Stavanger Daily Demand Profile 99

Figure 4.18 – Mode Share: Scenario C Oslo – Stavanger via Drammen, Porsgrunn, Arendal, Kristiansand

2024 (Oslo-Stavanger) 103

Figure 4.19 – Highest abstraction of journeys: Scenario C Oslo –Stavanger (via Drammen, Porsgrunn,

Arendal, Kristiansand) 2024 103


Figure 4.21 – Mode Share: Scenario D Oslo – Stavanger via Porsgrunn and Kristiansand 2024 (Oslo-

Stavanger) 106

Figure 4.22 – Highest abstraction of journeys: Scenario D Oslo – Stavanger (via Porsgrunn and



Figure 4.24 – Scen A (2024) Trondheim Daily Demand Profile 109 Figure 4.25 – Scen B (2024) Trondheim Daily Demand Profile 110

Figure 4.26 – Mode Share: Scenario C Oslo – Trondheim via Gardermoen, Hamar, Lillehammer and Otta

2024 (Oslo/Akershus-Trondheim) 114 Figure 4.27 – Highest abstraction of journeys: Scenario C Oslo – Trondheim (via Gardermoen, Hamar,

Lillehammer and Otta) 2024 114 Figure 4.28 – HSR demand by originating zone (annual) and point of boarding (daily) 115

Figure 4.29 – Mode Share: Scenario D Oslo – Trondheim via Gardermoen 2024 (Oslo/Akershus-Trondheim)117

Figure 4.30 – Highest abstraction of journeys: Scenario D Oslo – Trondheim (via Gardermoen) 2024 118

Figure 4.31 – HSR demand by originating zone (annual) and point of boarding (daily) 119 Figure 4.32 – Scen A (2024) Stockholm Daily Demand Profile 121

Figure 4.33 – Scen B (2024) Stockholm Daily Demand Profile 122

Figure 4.34 – Mode Share: Scenario C Oslo – Stockholm via Lillestrøm and Kongsvinger 2024

(Oslo/Akershus-Stockholm) 125

Figure 4.35 – Highest abstraction of journeys: Scenario C Oslo – Stockholm (via Lillestrøm and Kongsvinger)

2024 126

Figure 4.36 – Mode Share: Scenario D Oslo – Stockholm via Lillestrøm 2024 (Oslo/Akershus-Stockholm) 128

Figure 4.37 – Highest abstraction of journeys: Scenario D Oslo – Stockholm (via Lillestrøm) 2024 128

Figure 4.38 – Scen A (2024) Gothenburg Daily Demand Profile 130

Figure 4.39 – Scen B (2024) Gothenburg Daily Demand Profile 131

Figure 4.40 – Mode Share: Scenario D Oslo – Gothenburg non-stop 2024 (Oslo/Akershus-Gothenburg) 134

Figure 4.41 – Highest abstraction of journeys: Scenario D Oslo – Gothenburg (non-stop) 2024 135

Figure 5.1 – Incremental HSR journeys by corridor Scenario D over Scenario C (2024 estimates,

percentage) 141



Appendices

A. NSB Zone definitions (station groupings) 143

B. Assumed enhancements in Do Minimum matrices 144

B.1 Do Minimum: road enhancements 144

B.2 Do Minimum: Classic Rail enhancements 144

B.3 Do Minimum: Changes to levels of service on other modes (air, bus and ferry) 144

C. Demand Tables (future year journeys by mode) 145

C.1 Oslo – Bergen 146

C.2 Stavanger – Bergen 148

C.3 Oslo – Stavanger 149

C.4 Oslo – Trondheim 151

C.5 Oslo – Stockholm 152

C.6 Oslo – Gothenburg 153

C.7 County-to-county Matrices 154



Executive Summary Introduction

Jernbaneverket (JBV) has appointed Atkins to undertake Market Analysis to inform the study into

High Speed Rail (HSR) improvements in Norway. This report provides outputs from the demand

forecasting (Subject 1) work undertaken to support the market analysis. The existing passenger

market has been assessed and a model has been built to forecast the amount of demand that

might transfer from other modes to HSR and be generated as a result of the improvements.

The demand forecasts are an important input into the socio-economic assessment of the

proposed improvements. The forecast use of the improved services and shift from other modes

are used to quantify the revenue and monetised benefits of the improvements, which are

compared to the costs of building the scheme to understand which improvements are

economically worthwhile.

A range of potential improvement scenarios are being considered, some are relatively minor

upgrades to existing services (Scenarios A and B) and some are more aggressive, providing a

fundamental enhancement to the rail services which is akin to a new alternative mode of travel

(Scenarios C and D):

Scenario A – a continuation of the current railway policy and planned improvements, with

relatively minor works undertaken (the reference case to which the other upgrades listed

below are compared);

Scenario B – a more offensive development of the current infrastructure;

Scenario C – major upgrades to the current infrastructure achieving high-speed concepts;

and

Scenario D – building of new separate HSR lines.

The Underlying Market

The improved HSR services connect five key Norwegian cities: Oslo, Stavanger, Bergen,

Trondheim and Kristiansand. Services towards Gothenburg and Stockholm are also being

considered. There are smaller urban areas between these key cities that could also be served by

the services if there is adequate demand. Our demand analysis has focussed on the long-

distance market. Shorter distance flows to and from Oslo are considered by the parallel InterCity

Study, and are not included in our analysis.

Current long distance travel between these cities (trips of over 100km between the city pairs) is

shown in the table below together with mode and journey purpose split.

It is noticeable that travel by car is relatively limited as this table present travel between city pairs

only. For long-distance travel from areas outside the cities, car travel is much more dominant,

particularly for leisure travel.

About 65-70% of the trips between Oslo and the major cities of Bergen, Stavanger and

Trondheim are leisure trips, although on the Bergen – Stavanger corridor the business market is

more dominant than on the other routes. Air travel dominates the business market for long

distance travel with 74% of business trips between these cities being made by air.



Route Rail Distance

(km)

Total Trips (2010) A

ir

Cla

ssic

rail

Car

Coach

Busin

ess

Leis

ure

Oslo – Bergen 484 337,000 45% 28% 23% 4% 35% 65%

Oslo – Stavanger 599 171,000 50% 15% 31% 4% 36% 64%

Oslo – Kristiansand

365 121,000 23% 22% 39% 16% 29% 70%

Bergen – Stavanger

192,000 35% 1% 54% 9% 41% 59%

Oslo – Trondheim 553 277,000 47% 17% 31% 4% 33% 67%

The mode share of air is most dominant on the longest distance routes. This is driven by journey

times and passengers travelling by air having a higher value of time than those travelling by other

modes. Frequency of service will also contribute to higher volumes of business travel choosing

air travel given classic rail, for example, only provides four or five services a day between the

main centres where as there are up to 28 flights per day. For shorter distances (e.g. Oslo –

Kristiansand) air is less dominant.

By contrast, car dominates the leisure market with 45% of long distance leisure trips made

between these city pairs made by car. 25% of the city-city leisure trips are made by air, 22% by

rail and just 8% by coach. Classic rail has low mode share for business travel (10-20%) but

carries more leisure passengers (20-30%).

From the analysis of current service provision, it is clear that air travel provides the best service

for inter-urban users on the majority of corridors, with over 20 flights a day between Oslo and

Bergen, Trondheim and Stavanger. On the Kristiansand and Gothenburg corridors, the air

service is not as frequent, presumably due to the higher quality roads on these routes and the

more manageable journey time by car. There are also more frequent coach services on these

corridors. The current level of service for rail is presently low for the main long distance routes,

with approximately 5 trains a day between the key cities. For more local travel there is a more

frequent service. Fares tend to be higher for air compared with rail and coach, although if booked

in advance air fares are broadly similar to rail and coach fares booked on the day.

In terms of attraction from current services to the new high speed services, HSR in other

countries has tended to compete with air services and therefore is dominated by business users,

with a strong need for reduced journey times. Leisure passengers on the whole find car travel to

be the most convenient mode of transport.

For HSR to compete effectively with car travel, provisions will need to be made to ensure strong

connectivity to HSR stations and careful consideration of station location must be made. There is

a delicate balance between optimising end-to-end journey times for business air users, while at

the same time introducing enough intermediate stops to attract leisure users who would currently

travel by car.

The tourism market may have some impacts on HSR demand, although the most popular

attractions tend to be away from cities. The seasonal nature of the tourism leads to variations in

demand, and it may be difficult to attract this market to HSR beyond the core city-to-city markets.

Given that any HSR scheme is likely to be implemented in several years‟ time, this report

analyses expected levels of growth in travel demand even before HSR is implemented. Growth

between current levels and future levels has been established using the NTM 5 model. In the

medium term, rail demand is assumed to growth at around 2 to 3% per annum depending on the



route and air demand is expected to grow at around 2% per annum. This will increase the

potential market for HSR services.

From an international benchmarking review, we have established that the size of the potential

market for HSR in Norway is much smaller than the HSR markets already established in

countries such as France and Germany, although the size of the potential market is more similar

to that of Sweden. From experience in other European countries where HSR is already well

established, there has sometimes been almost total abstraction from air on routes served by

HSR as rail journey times have been dramatically reduced and major rail stations are located

more conveniently than the airports.

HSR Proposed Routes

The Demand Potential for High Speed Rail Services

Within Phase 2 of the overall High Speed Rail Assessment project, the Market Analysis work has

developed a forecasting approach which can be used to test detailed options in Phase 3 of the

project.

For marginal improvements to the existing services, the NTM 5 long distance demand forecasting

model is appropriate for forecasting demand on the improved services. However, for the more

aggressive improvements giving a step change in rail services, a more suitable new model was

built. The new model used outputs from a Stated Preference (SP) Survey (Subjects 2 and 3 of

the Market Analysis work) to determine passenger‟s likely response to the new services. The

scope of the demand forecasting work is the long distance travel market.



A number of example scenarios were tested to demonstrate the suitability of the model for

forecasting, give initial views on the potential size of HSR markets and allow options to be further

developed during Phase 3 of the study.

Initial forecasts were developed across the six corridors, assuming levels of service provided by

JBV across a range of levels of service improvement from Scenario A (only marginal, planned

improvements) to Scenario D (new high speed rail alignments). For the purposes of this report, it

was assumed that HSR services would have the same fares as current air services and that

there would be no reduction in either air or existing rail services as a result of introduction of

HSR. Therefore, the forecasts represent a base on which it is expected that demand may

increase as options are developed during Phase 3. In addition, the market for InterCity

commuting into Oslo was specifically excluded from consideration, as it is subject to a separate

study by JBV.

The indicative results from the initial set of modelling tests carried out are set out below. For

Scenario D only, a range of demand and revenue has been presented, on the basis of different

fare assumptions. It is important to note that when lower fares are assumed, the demand is

higher but the overall revenue is reduced. The higher revenue shown corresponds to the option

where HSR fares are assumed to equal air fares, as even though there are less passengers, the

total yield is forecast to be higher. Further testing of more combinations of alternative

frequencies, journey times, stopping patterns and fares will be carried out in Phase 3 to add to

this initial set of tests:

Between Oslo and Bergen, with the fastest journey times (Scenario D, 2 hours 30 non-stop

compared to 6 hours 30 currently), 1.5m to 2.5m trips per year are attracted to the HSR services

depending on the fare assumptions used, generating up to 1.3bn NOK per annum. Total rail trips

on the corridor would correspond to 2.1m to 3m trips per year. If journey times are reduced to

approximately 4 hours 30 minutes (Scenario C), around 1.1 million trips per year are attracted

(assuming stops at Hønefoss, Gol and Voss). Compared to Scenario D slightly more trips are

abstracted from car and slightly fewer from air.

Between Oslo and Stavanger via Kristiansand, Scenario D generates 2.0m to 3.1m trips per

annum and up to 1.7bn NOK per annum on HSR services. Services would take 2 hours 30

minutes plus stopping time (compared to 7 hours 40 today) with stops at both Kristiansand and

Porsgrunn. Total rail trips in the equivalent corridor would be around 3.3m to 4.4m trips/year. The

slower Scenario C service, taking 5 hours 30 minutes in total, stopping at all key locations,

generates 1.3m trips and 0.7m NOK per annum. Although the faster Scenario D services are

forecast to attract 0.7m to 1.8m more trips per annum, the slower stopping services perform

relatively well despite significantly slower end-to-end journey times. The trade off between the

revenue generated and the costs of the infrastructure service should be investigated in Phase 3

to see which the optimum service is as the infrastructure for the faster services could cost

considerably more than the slower one. Consideration should also be made of the interactions

with the inter-city study because of the indirect potential to improve journey times between Oslo

and Southern Norway.

There is a proposed “Y-shaped” route from Oslo to both Bergen and Stavanger. This service

attracts 2.5m to 4.1m trips per annum (with a total rail market of 4.4m to 6m trips/year); this is

less than the combination of the alternative Bergen and Stavanger routes, which together attract

about 3.5m to 5.6m demand, as they serve more intermediate markets than the Haukeli route.

Up to 2.5bn NOK is generated per year on HSR services with this option.

Introducing a service from Bergen to Stavanger attracts 0.7m-0.9m HSR trips per annum

stopping at Haugesund, generating up to 0.5bn NOK. The engineering to produce the link is likely

to be particularly challenging given the proximity to the coastline and requirement to cross fjords.

In Phase 3 the costs associated with this will be understood and, along with all other options,

consideration of whether the generated revenue and benefits can justify the costs.



Improving journey times between Oslo and Trondheim from 6 hours 40 minutes currently to 2

hours 45 minutes is expected to attract around 1.8m to 2.2m trips per annum on HSR services

(2.8m to 3.2m total rail trips per year on the corridor), stopping at Gardermoen Airport, and

generates up to 1.3bn NOK per annum. Gardermoen Airport is a key driver of HSR demand; we

recommend that options for HSR to Bergen and Stavanger be developed to include direct

connections to the airport to increase HSR demand further.

On routes towards Stockholm and Gothenburg, current demand forecasting shows around 0.8-

1 million trips would be attracted to HSR services (a total of on each of the routes and up to

0.7bn NOK revenue for each corridor. The HSR route to Stockholm takes 3 hours compared to

the 6 hour service today and the journey time to Gothenburg is assumed to reduce from about 4

hours to 2 hours and 30 minutes. The route to Gothenburg attracts the most demand, although

limitations on available data means that caveats have to be applied to the robustness of this

forecast.

For the less significant journey time improvements of Scenario B compared to Scenario A

(usually saving about an hour from current journey times), about 0.1m rail trips are attracted on

the corridors from Oslo to Bergen, Stavanger and Trondheim. Routes for Scenario B towards

Sweden were tested but the impact on demand was negligible due to the lack of demand within

scope of the forecasting model.

Mode Shift

For the smaller journey time improvements in Scenario B 90% of the additional rail demand

attracted is either newly generated trips or transfer from car. On the route to Bergen, 78% of

demand is generated and 14% transfers from car. On routes to Stavanger and Trondheim,

almost 60% of the attracted rail trips are generated and around 30% is from car. Less than 5% is

transferred from coach or ferry and around 5% is from air.

For the faster services in Scenarios C and D tested so far, generally a third of the demand

attracted to HSR is newly generated trips, 40% is from air, 15-20% from car and less than 10%

from current rail services and coach. The clear exceptions to this are:

60% of the demand attracted to services to Trondheim that stop at Gardermoen is from air;

between Bergen and Stavanger less of the HSR demand attracted comes from air (34%),

more is transferred from car (24%) and none comes from rail where there currently is no

service; and

A significant proportion of demand to Gothenburg transfers from car (67%) and almost none

transfers from air. For the routes to Stockholm less than 10% is attracted from car and a

much more (around 50%) from air. On routes to Stockholm about 40% of HSR trips are

generated but fewer on the route to Gothenburg (about a third). These conclusions also

should be treated with caution given the current limitations of the Swedish demand data.

Journey Purpose

For passengers attracted to the new HSR services, generally 60-65% of trips are business trips

and 35-40% are leisure trips showing that HSR competes more with air for the market attracted

to higher speeds and the service quality offered by HSR. For slower services the percentage of

business users is at the bottom end of this range. For example, Oslo to Bergen, for Scenario C

services 59% of demand is business but for scenario D services, 63% is business. The key

exceptions to this are:

Between Oslo and Stavanger business travel is at the higher end of the spectrum at 66% for

Scenario D services and 64% for scenario C;

From Bergen to Stavanger, business travel is significantly higher at 74% despite there being

a lower transfer from air to HSR;



The service to Gothenburg has much higher business demand at almost 80% despite almost

no transfer from air; and

Routes to Stockholm have much less business travel at around 30% of demand, despite a

more significant transfer from air.

For the smaller improvements in journey times from Scenario A to B, 25-30% of the demand

attracted to rail services is business trips, in contrast to the 60-65% business trips with the more

significant increases in journey times in Scenarios C and D.

Next Steps

In Phase 3 further refinements to the modelling and scenario tests will be made in light of a

review of the outputs from Contract 1 – Technical and Safety Analysis, and Contract 2 – Rail

Planning and Development. Recommendations from the route alignment and technical feasibility

studies will help inform more detailed corridor alignments, stopping patterns and journey times.

Further combinations of stops and frequencies can be tested to find the optimum services

comparing with the costs to understand the financial viability alongside the demand generated.

There will also be interaction with Contract 6 – Finance and Economics, in order to incorporate

the costs of each option and calculate the relative benefits of each option. There will be an

iterative process between the demand and revenue forecasting and socio-economic assessment.

It will be important to consider services serving the main airports, particularly Trondheim Værnes

and Sandefjord Torp, as the routes serving Gardermoen picked up a significant amount of

demand.

The trade off of the lost demand from Scenario C type improvements with the lower costs should

be a focus to understand whether the incremental benefits of the significantly faster speeds

associated with Scenario D are justified given the additional costs.

Interaction between the scenarios defined in this study and those being pursued in the Intercity

study should be examined to understand if there are additional benefits brought about by

connectivity between HSR and improved local rail services, especially in the south-east of

Norway, in the counties of Oslo, Østfold and Vestfold.

In addition, further refinements to the forecasting approach will be made, to take advantage of

any new data available – particularly relating to travel to and from Sweden and the long-distance

car travel market.



1 Introduction 1.1 Background

Jernbaneverket has been mandated by the Norwegian Ministry of Transport and

Communications to assess the issue of High Speed Rail (HSR) lines in Norway. There is a

National Transport Plan covering the period from 2010-2019 which includes relatively minor

enhancements to the railway network. The ministry wishes to understand if going beyond this

and implementing a step change in rail service provision in the form of higher speed concepts

could “contribute to obtaining socio-economically efficient and sustainable solutions for a future

transport system with increased transport capacity, improved passability and accessibility”.

Previous studies have been carried out looking into HSR in Norway and there are various

conflicting views. The aim of this study is to provide a transparent, robust and evidence based

assessment of the costs and benefits of HSR to support investment decisions.

The study has been divided into three phases.

In Phase 1, which was completed in July 2010, the knowledge base that already existed in

Norway was collated, including outputs from previous studies. This included the studies that

already were conducted for the National Rail Administration and the Ministry of Transport and

Communication, but also publicly available studies conducted by various stakeholders, such

as Norsk Bane AS, Høyhastighetsringen AS and Coinco North.

The objective of Phase 2 is to identify a common basis to be used to assess a range of

possible interventions on the main rail corridors in Norway, including links to Sweden. The

work in Phase 2 uses and enhance existing information, models and data. New tools have

been created where existing tools are not suitable for assessing high speed rail.

In Phase 3 the tools and guiding principles established in Phase 2 will be used to test

scenarios and options on the different corridors. This will provide assessments of options and

enable recommendations for development and investment strategies in each corridor.

This report is a component of the Phase 2 work.

The principles established in Phase 2 are to be used to test four scenarios:

Scenario A – reference case. This is a continuation of the current railway policy and planned

improvements, with relatively minor works undertaken, as shown in the National Transport

Plan from 2010-2019 This forms the „Do Minimum‟ scenario against which the other scenarios

will be compared.

Scenario B – upgrade. A more offensive development of the current infrastructure, with more

improvements outside the „Intercity‟ area;

Scenario C – major upgrades achieving high-speed concepts. This is to be based on an

aggressive upgrade of the existing network to provide a step change in journey times; and

Scenario D – new HSR. This involves the implementation of newly built, separate HSR lines.

The improvements are being considered on six corridors:

Oslo – Bergen;

Oslo – Trondheim;

Oslo – Kristiansand and Stavanger;

Bergen – Stavanger;

Oslo – Stockholm (to Skotterud in Norway); and



Oslo – Gothenburg (to Halden in Norway).

The scenarios will be considered in relation to the long distance travel market, for example for

journeys over 100km in distance. Other studies, such as the Intercity Study will look at initiatives

for shorter distance travel at a more regional level. Various route alignments, stop patterns,

station designs, speed standards and fares will be tested. It will be necessary to assess

conditions related to income and costs, environmental concerns, energy consumption,

maintenance under winter conditions and the procurement and operational organisation of the

services and infrastructure.

1.2 Overall Context of the Market Analysis Contract

To achieve Phase 2 of the study, Jernbaneverket has commissioned 6 Contracts:

Technical and Safety Analysis;

Rail Planning and Development;

Environmental Analysis;

Commercial and Contract Strategies;

Market Analysis; and

Financial and Economic Analysis

WS Atkins International Ltd (Atkins) is assisting Jernbaneverket in two of the contracts: Market

Analysis and Financial and Economic Analysis. This report is part of the Market Analysis

Contract.

The Market Analysis contract consists of five Subjects:

Subject 1: Demand potential for high speed rail services in Norway;

Subject 2: Analysis of expected amount of ticket revenues;

Subject 3: Passengers choice – preferences for travel and means of transport;

Subject 4: Location and services of stations / terminals; and

Subject 5: Market conditions for fast freight trains.

The purpose of the Market Analysis Contract is to establish the size of the potential HSR

passenger and freight markets under different HSR scenarios. This involves identifying the

current market and its projected growth, mode share and the preferences and priorities of those

markets. The current market is used as a basis, together with expected willingness to pay for

new services, to forecast how much of this market would be attracted to new HSR scenarios, and

how much additional demand may be induced.

This report provides the outputs for Subject 1.

1.3 Purpose of Subject 1: Demand Potential for HSR in Norway

The objective of Subject 1 is to identify the potential markets that might switch to new HSR

services under the different scenarios proposed, on each of the different corridors, and forecast

the passenger use of these services. This includes the passengers who would transfer from an

existing mode (air, car, existing rail services, coach or ferry) as well as the demand generated as

a result of the investment.

The outputs from the demand forecasting are used to predict the revenue and socio-economic

impacts of the proposed investments. The revenue is combined with cost estimates to determine

the commercial viability of the investment and together with demand forecasts are used to help

specify the infrastructure and rolling stock required. The socio-economic benefits, including

environmental impacts, are calculated using outputs from the demand forecasting tool. These



benefits are combined with costs and revenue as well as other non-quantified assessments to

provide the overall socio-economic assessment of the proposed investments. All of these outputs

are used as a basis for making investment decisions and development plans.

At this stage, the outputs from Subject 1 will be outline forecasts for generic options to help

shape the priorities for High Speed development and compare the scenarios proposed. In Phase

3 of the study, the forecasts can be updated and refined to provide forecasts against more

specific alignments (and therefore more accurate journey times) and station locations, for

example.

1.4 This Report

This report provides outputs from analysis by mode, by journey purpose and by corridor, of the

current (2010) long distance travel market in Norway, as well as forecasts of the future changes

in long distance travel expected under each of the improvement scenarios, including the

Scenario A reference case („continuation of current policies‟).

For improvement Scenarios B, C and D (as defined in Section 1.1), the forecasts of incremental

rail demand and revenue over the reference case are subdivided into (a) journeys abstracted

from air, car, coach and (where appropriate) classic rail, and (b) pure generation, i.e. additional

mobility induced by the improved journeys.

The reporting structure is intended to provide a clear and comprehensive summary of the

demand implications for each mode of the potential scenarios for each corridor, allowing robust

conclusions to be drawn.

Example scenarios have been developed, in agreement with JBV, representing a range of

journey time improvements across each of the main corridors. However, we emphasise that

these only represent an initial view as to the definition of each potential intervention in terms of

HSR journey times, fares, stopping patterns and service frequencies, and make conservative

assumptions on the response of airlines and changes to existing rail services. The next phase of

work will refine these scenarios to increase demand and revenue forecasts, as well as develop

the options in light of cost, economic benefit and environmental assessment information.

It should also be noted that detailed reporting of the approach applied to forecasting and

modelling is provided in a complementary Model Development Report. The exception is RAND‟s

description of the Stated Preference analysis which is provided in the Final Report for Market

Analysis Subjects 2 and 3.

The remainder of this report has the following chapters:

Chapter 2 - Current travel market;

Chapter 3 - Future travel market (Do Minimum Scenario, Scenario A);

Chapter 4 - HSR Demand and Revenue Forecasts (Scenarios B, C and D); and

Chapter 5 - Conclusions.



2 Current Travel Markets 2.1 Introduction

This chapter provides a detailed analysis of the current long-distance travel market in Norway, to

provide a background to the planning and forecasting of potential HSR lines. The focus is on the

six main transport corridors that are being considered in the HSR study. There are three

elements to the analysis:

Size of existing travel markets – analysis of current travel demand for end-to-end journeys

and intermediate travel along corridors, as well as consideration of qualitative factors such as

seasonal variation of travel;

Comparison of product quality – reviewing the existing travel opportunities available by air,

road, rail and sea, as well as comparing between the different modes; and

International benchmarking – analysis of corridors in other countries where HSR has already

been introduced.

The analysis of present travel markets in Norway will help inform the basis for consideration of

the potential for HSR development in Norway. This is achieved by determining the size of the

markets for business and leisure travellers, the mode of transport used and associated quality of

each mode. The size of the markets for each transport mode can then be compared against the

current travel opportunities for each mode, as well as HSR markets in other European countries.

Limitations on the quality of data available on movements between Norway and Sweden mean

that analysis is limited to the relevant internal corridors.

2.2 Size of Existing Travel Markets

This subsection presents a review of the current demand for travel along the six principal

transport corridors in Norway, each of which may have sufficient demand to justify significant

future improvements to rail services.

The aim is to facilitate comparison of the relative size of current journey volumes within each

corridor with disaggregation by mode (i.e. domestic air, „classic‟ rail, car and bus/coach), and by

journey purpose (i.e. business versus non-business travel). Within each corridor it is also

important to identify travel between Oslo and the other major cities (typically end-to-end trips) to

allow the relative importance of journeys to/from other towns to be assessed.

This section examines:

The distribution of population and income across Norway as a whole;

Existing demand for travel between the largest cities‟ immediate urban areas;

Existing demand for travel between wider city region catchment areas; and

Demand driven by tourism that may to a significant extent be seasonal.

The distinction between core urban areas and wider catchments is important, as it reflects the

different attractiveness of air, rail and road depending on distance to urban centres and transport

gateways. For example, future HSR services with limited stops are liable to have longer access

and egress distances than classic rail, with stations displaying regional catchment areas akin to

those of the major airports. Meanwhile, the incidence of car use between any pair of urban

centres will tend to increase with the diameter of the HSR stations‟ assumed/defined catchment

areas.



2.2.1 Population and Income Distribution

Norway is a relatively sparsely populated country due to the large mountainous regions and

fjords which limit development of urban areas in vast areas of the country. The population of

Norway is predominantly focused in the south-east of the country, where the topography is far

less mountainous, and along the coastline.

Figure 2.1 below shows the population density in Norway in 2010 by municipality.1 This figure

illustrates the large sparsely populated areas in the centre of Norway, and the high concentration

of population around Oslo. There are also clearly areas of sizable population along the south

and west coastline. This demonstrates that the market for travel in Norway is mainly focussed in

small areas, particularly in the south-east of the country, while there are large areas where there

is relatively little demand. The areas of high population density around the cities and large areas

of low density show that travel from major cities is predominantly either local travel within the city

and its suburbs, or long-distance travel to other cities.

Figure 2.2 illustrates the average income in Norway broken down by municipality.2 The figure

demonstrates that the average income is generally higher in the areas of high population density,

but lower within main cities of Norway. This illustrates the point that areas surrounding cities

tend to have the highest levels of income: this could potentially affect the willingness to pay fares

for HSR services that are higher than existing rail services, and the associated financial viability

of HSR.

The distribution of population and income shows that the predominant demand for HSR is likely

to be for city-to-city travel. Another implication for HSR is that the highest willingness to pay for

time savings is generally in cities and surrounding suburban areas, so the positioning of stations

and connectivity with local transport will highly influence the implementation of any potential HSR

service.

2.2.2 Long-distance Travel Demand: City-to-city

This section presents the annual demand for travel between the urban areas of the five major

cities, which form the key destinations of the HSR network: Oslo, Bergen, Stavanger, Trondheim

and Kristiansand. City-to-city travel is likely to form a large proportion of the total long-distance

travel in Norway, due to the distribution of population described above, and that these cities form

the main centres of business.

Data sources

Demand between cities considered here is annual demand for 2010 derived from the NTM5

model. Rail and air demand matrices from this model have been calibrated using Norwegian

State Railways (NSB) ticket sales data and Avinor passenger count data, respectively. The

NTM5 zones have been aggregated up to form a new HSR zoning system for presentation

purposes3.

1 Population data from Statistics Norway (Jan 2010):

http://www.ssb.no/english/subjects/02/01/10/folkber_en/tab-2010-12-16-01-en.htmland

Municipality areas from the Norwegian Mapping Authority (2010): http://www.statkart.no/nor/Land/Fagomrader/Arealer_og_tall/ 2 Source: Statistics Norway

http://statbank.ssb.no/statistikkbanken/Default_FR.asp?PXSid=0&nvl=true&PLanguage=1&tilside=selecttable/hovedtabellHjem.asp&KortnavnWeb=inntgeo 3 See separate technical note: TN2 Proposed Zoning System



Figure 2.1 – Population density in Norway by municipality (2010)



Figure 2.2 – Average (median) net income in Norway by municipality (2008)



It should be noted that the car and coach demand data has been taken directly from NTM5 and

has not yet been validated against traffic counts. As the NTM5 model is not calibrated on a

detailed level, this means that the data for car and coach demand may be subject to

inaccuracies. It is intended that car data in particular will be adjusted for Phase 3 of the work

with real traffic counts from the Norwegian Roads Authority (if this can be made available) in

order to ensure the accuracy of the data.

Figure 2.3 below illustrates the zones included in the calculation of flows from major cities. The

cities and flows are defined in terms of travel between municipalities (i.e. „kommuner‟). For

example, „Oslo - Bergen‟ includes journeys from the eight urban districts within Bergen

municipality to Oslo‟s 17 urban districts. However, journeys from Bergen‟s neighbouring

municipality, Vaksdal, to Bærum, which neighbours Oslo, are excluded.

As described above, the population in Norway is concentrated in the five largest cities. However,

Oslo has a large commuter belt, including the municipalities within the county of Akershus. It is

hence worth noting when analysing the demand for each route that these suburbs are excluded

from the city-to-city journeys.

Total Demand Analysis

Table 2.1 shows the total travel demand for each city-to-city flow routes, disaggregated by

transport mode. Oslo-Bergen is the largest market; these cities constitute the two largest

population and employment centres.

Table 2.1 – Total annual demand for key corridors in Norway for main transport modes (2010)

Route Air Classic Rail

Car Coach Total

Oslo – Stavanger 85,000 26,000 53,000 7,000 171,000

Oslo – Bergen 150,000 96,000 77,000 13,000 337,000

Oslo – Trondheim 130,000 48,000 87,000 12,000 277,000

Oslo – Kristiansand 28,000 27,000 47,000 19,000 121,000

Bergen – Stavanger 67,000 2,000 104,000 18,000 192,000



Figure 2.3 – City areas included in the calculation of demand for city-to-city travel



It is also apparent that air is the dominant mode on the long-distance corridors. This is further

illustrated in Figure 2.4, which compares the mode significance by corridor. The key

observations are:

Demand is highest for air travel on the longer distance routes, namely Oslo to Bergen and

Trondheim;

Oslo – Kristiansand has higher car, rail and coach flows in relation to air travel, probably due

to the shorter distance from Oslo negating the overall journey time saving of air travel;

There is significantly higher demand for rail travel on the Bergen route, which may be

influenced by the popularity of the Oslo-Bergen rail line as a tourist attraction due to the

attractive scenery along sections of the route;

The Bergen-Stavanger route has significantly higher car flows, influenced by the lack of a

direct rail route and limited air services; and

Demand for coach travel is significantly lower than rail and air travel on all routes except for

the Oslo – Kristiansand corridor, where coach travel times and frequencies are significantly

more competitive with air due to better road infrastructure.

Figure 2.4 – Total demand for each mode by corridor

Business Demand

The demand for travel presented in Table 2.1 can be further disaggregated into business and

leisure trips. Table 2.2 presents demand between the major cities in Norway for business travel

only, indicating the scale of high value, work-related journeys currently travelling from end-to-end

of each corridor.

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

Air Classic Rail Car Coach

Nu

mb

er

of

jou

rne

ys p

er

year

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger



Table 2.2 – Annual business demand for key corridors in Norway for main transport modes (2010)


Car Coach Total

Oslo – Stavanger 51,000 5,000 6,000 <1000 62,000

Oslo – Bergen 87,000 22,000 8,000 2,000 118,000

Oslo – Trondheim 74,000 8,800 7,000 1,000 91,000


Bergen – Stavanger 52,000 <1000 22,000 4,000 78,000

The table shows that the Oslo-Bergen route has the highest volume of end-to-end business

travel, even when Kristiansand and Stavanger are jointly considered as a single corridor. This

reflects the high levels of business activity in the Bergen area.

The high levels of car and air demand on the Bergen – Stavanger corridor reported in the NTM5

model seem unrealistic: further analysis of this market needs to be undertaken to establish the

reasonableness of this figure, but no independent data is available to verify this.

Figure 2.5 – Business demand for each mode by corridor (2010)

Figure 2.5 compares the significance of modes on each corridor. The overwhelming majority of

business travel is conducted by air for all flows except Oslo-Kristiansand. This reflects the higher

value of time place on work related journeys, as air is the quickest mode of transport for long-

distance journeys. There is significant business rail travel on the Oslo-Bergen route and car

travel on the Bergen-Stavanger route. Business coach travel is negligible on all routes.

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000


Nu

mb

er

of

jou

ne

ys p

er

year

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger



Figure 2.6 presents the mode shares on these corridors and suggests:

Air travel dominates between Oslo and all the major cities. Kristiansand is an exception,

where the city‟s relative proximity to the capital allows surface modes to capture almost half

of the market;

There is higher market share for rail travel (18%) between Oslo and Bergen than between

Oslo and Stavanger or Trondheim. The higher share seems to be primarily at the expense of

air travel; and

There is negligible rail demand between Bergen and Stavanger as there is no direct rail route

between the two cities. Indeed, any residual demand is likely to be a result of NTM5 model

estimation and should not be noted as significant as in reality there would be no rail travel on

this route. The result is a higher proportion of travel on other modes, in particular a shift to

travel by car.

Figure 2.6 – Mode share for city-to-city business trips by corridor (2010)

Leisure Demand

The leisure segment of the travel market carries a lower value of time and generally larger group

sizes, therefore different mode choices may be expected than for business travel. Table 2.3

presents demand for leisure travel between the main urban centres.

Table 2.3 – Annual leisure demand for key corridors in Norway for main transport modes (2010)


Car Coach Total

Oslo – Stavanger 35,000 21,000 47,000 6,000 109,000

Oslo – Bergen 63,000 75,000 70,000 12,000 219,000

Oslo – Trondheim 56,000 39,000 80,000 11,000 186,000


Bergen – Stavanger 16,000 1,000 82,000 14,000 113,000

Bergen is again the largest market, although to a lesser extent than for business; the leisure

volume is only 18% higher than that for Trondheim, compared to a figure of 29% for business.

0% 20% 40% 60% 80% 100%

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger

Air

Classic Rail

Car

Coach



The share of air travel is much lower for leisure journeys than for business, with a much higher

proportion using car and classic rail as shown in Figure 2.7.

Figure 2.7 – Leisure demand for each mode by corridor (2010)

Figure 2.8 – Mode share for city-to-city leisure trips by corridor (2010)

Figure 2.8 presents the mode shares on these corridors and suggests that:

Leisure demand is more evenly shared between the different modes of transport, with

reduced dominance of air travel. This is to be expected, as leisure journeys are generally

more price sensitive, and likely to be made as part of larger groups (particularly families).

Both of these factors increase the probability of car use over air and rail;

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000


Nu

mb

er

of

jou

rne

ys p

er

year

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger

0% 20% 40% 60% 80% 100%

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger

Air

Classic Rail

Car

Coach



Car demand has the highest mode share, except for Oslo to Bergen, where the leisure

market is split almost equally between car, train and air. The scenic nature of the Bergen

route may contribute to its higher share for the leisure segment; and

Car and coach demand is particularly high on the shorter distance routes between Oslo and

Kristiansand, and Bergen and Stavanger. The air demand on these routes is far lower than

the longer distances.

In summary for city-to-city travel:

Oslo-Bergen is the largest market for travel, followed by Oslo-Trondheim and Oslo-

Stavanger;

For business trips air is the dominant mode, despite the need to travel out of cities to airports.

This is because air is much faster than any other mode and business trips attach a high value

to time; and

For leisure trips the mode share is more balanced. On the Bergen route in particular classic

rail takes a much larger market share.

2.2.3 Long-distance Travel: Wider Catchment Area Analysis

The previous section studied demand for travel between the primary cities‟ urban areas but

existing airports have a much larger catchment area, encompassing entire regions of the country.

HSR stations, given adequate intermodal connections (in particular car parking) could perform a

similar function to airports in attracting demand from a large catchment area. Hence, this section

studies the market for travel between regional corridors.

The demand for air travel in this section is based on ticket sales data supplied by Avinor for 2009

and covers all of corridors where HSR is also proposed. In contrast to the data reported above,

these figures are airport to airport passenger journeys and do not reflect the distribution of trips

between surrounding areas.

For this analysis of corresponding car and rail demand from NTM5, regional catchment areas

have been drawn around the five key urban areas for the purpose of a direct comparison with the

air data. The catchment areas are shown in Figure 2.9. These large catchments reflect the

distance travelled to access airports today.



Figure 2.9 – Wider catchment areas for Norwegian airports for the calculation of road and rail demand



Business

On a wider catchment area basis, business trips from region to region are still dominated by air

for the longer distances (Oslo – Bergen/Stavanger/Trondheim) but to a lesser extent than on city-

to-city trips – see Figure 2.10.

Figure 2.10 – Number of business trips by corridor and mode (2010)

The dominance of air travel will tend to increase with distance, reflecting the greater journey time

savings over other modes of transport. Volumes of business travellers exceed leisure travellers

by at least 20% on each of the air routes. Summing across all of these routes, the business

market exceeds the leisure market by over 50%.

The interaction of demand and supply and the resulting dominance of air travel can be confirmed

by comparing the number of air services per weekday (final column) with corresponding rail data

in Table 2.21 below.

Figure 2.11 presents the mode split for business demand confirming that car trips dominate the

interregional trips for the shorter routes.

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

Air Classic Rail Car

Nu

mb

er

of

jou

rne

ys p

er

year

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger



Figure 2.11 – Mode share by corridor for business trips (2010)

Leisure

Figure 2.12 demonstrates that the trend away from air use for leisure journeys is magnified when

considering wider catchment areas, with car tending to dominate on all corridors. This is to be

expected as the increased access times to airports – and rail stations – increases when the wider

catchment areas are considered.

Figure 2.12 – Number of leisure trips by corridor and mode (2010)

0% 20% 40% 60% 80% 100%

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger

Car

Air

Classic Rail

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

Air Classic Rail Car

Nu

mb

er

of

jou

rne

ys p

er

year

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger



It should be noted that the quality of NTM5 data for long-distance car journeys is of debatable

quality, with reports that the modelled data overstates use of car in this segment. Some caution

has to be applied to assumptions of potential HSR shift from car until further cross-validation data

is available.

Figure 2.13 suggests that the Bergen route has the highest proportion of leisure travellers by rail,

as was demonstrated for city-to-city travel. Air establishes itself at around 25% of the market on

the Oslo – Trondheim/Stavanger/Bergen routes.

Figure 2.13 – Mode share by corridor for leisure trips (2010)

Summary

Comparing the mode share for region-to-region against those for city-to-city travel documented

earlier in this report, it is clear that analysis using the large airport catchment areas significantly

raises the mode share of car. This is to be expected, because remote areas some distance from

the suburbs, let alone city centres, are unlikely to be well-served by public transport. Thus, the

incidence of car use will increase as the focus on cities is diluted.

For business trips however, it is clear that air is the dominant mode and is clearly carrying more

passengers than the existing classic rail network for passengers with a high value of time. This is

driven by journey times, but also by frequency of service. Classic rail only provides four or five

services a day between the main centres where as there are up to 28 flights per day (see Section

2.3).

2.2.4 Tourism Market

An important aspect of long-distance travel in Norway is the existence of a significant tourism

industry. There are two distinct tourism markets in Norway:

A winter tourism market based largely on access to ski resorts. This is a more disperse,

market largely focussed on travellers from Norway, Sweden and Denmark with a lower

proportion of international arrivals by air. Travellers often arrive by car and/or ferry and travel

to private ski chalets or resorts across southern Norway; and

A summer tourism market, with significant travel to the coast western Norway, particularly

“Fjordland” around Bergen. This has a larger proportion of international travellers arriving by

air, with potential to use HSR to access areas of Norway outside Oslo.

0% 20% 40% 60% 80% 100%

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger

Car

Air

Classic Rail



Figure 2.14 displays the location of the prominent ski resorts in Norway, as well as the

connecting transport networks.4 It can be seen that a large number of such resorts reside on

potential HSR corridors, in particular the Oslo-Bergen and Oslo-Trondheim routes.

4 Source: Visit Norway http://www.visitnorway.com/

Figure 2.14 – Location of major ski resorts in Norway



Summer tourism, especially to the fjords in western Norway and in the main cities, also provides

demand for leisure travel. Table 2.4 lists the top ticketed attractions in Norway by number of

visitors, while Table 2.5 shows the most popular natural attractions.

Table 2.4 – Top ten ticketed tourist attractions in Norway (2007)5

Cultural Attraction Location Visitors

Fløibanen (Venicular railway) Bergen 1,131,707

Holmenkollen ski jump and Ski Museum Oslo 686,857

Bryggen Bergen 583,510

Kristiansand Zoo and Amusement Park Kristiansand 532,044

Tusenfryd Ås 501,235

Flåm Railway Flåm 457,545

Hadeland Glassverk Jevnaker 431,400

Fredrikstad Fortress, Old Town of Fredrikstad Fredrikstad 372,360

Viking Ship Museum Oslo 314,560

Hunderfossen Theme Park Øyer/Lillehammer 270,500

Table 2.5 – Top ten free tourist attractions in Norway (2006)6

Natural Attraction Location Visitors

Vøringsfossen waterfall Eidfjord 655,000

Scenic road Trollstigen Åndalsnes 563,331

Kjosfossen Waterfall Flåm 457,400

World Heritage Site Geirangerfjorden Geiranger 423,643

Låtefossen Waterfall Odda/Hardanger 420,000

Steinsdalsfossen Waterfall Norheimsund/Hardanger 300,000

World Heritage Site Nærøyfjorden Aurland 297,038

Briksdalsbreen Glacier Olden/Stryn 280,000

National Tourist Road Sognefjellsvegen Lom-Luster 253,953

Scenic road Atlanterhavsvegen Averøy/Kristiansund 237,316

The presence of high volume ticketed attractions in Bergen, Oslo and Kristiansand may

contribute to the demand for trips between these centres, which could be carried by a HSR

network. In contrast, most natural attractions are unlikely to be accommodated by HSR as they

lie outside the major centres, as shown in Figure 2.15. Also shown is the number of international

tourist guest nights in accommodation establishments for the year 2009 for each county. HSR

may offer some possibilities in providing greater access for international travellers arriving by air

to gain access to areas outside of Oslo – particularly Bergen – through reduced travel times.

5 Source: Innovasjon Norge: http://www.innovasjonnorge.no/default.aspx

6 Source: Innovasjon Norge: http://www.innovasjonnorge.no/default.aspx



.

Figure 2.15 – Location of major tourist attractions and fjords in Norway and international guest nights

in 2009



Figure 2.16 shows the number of domestic guest nights in 2009.7 Both Figure 2.15 and Figure

2.16 demonstrate that the Bergen and Trondheim corridors attract the most tourist trips.

7 Source: Statistics Norway http://www.ssb.no/reiseliv_en/

Figure 2.16 – Location of major tourist attractions and fjords in Norway and domestic guest nights in

2009



Figure 2.17 shows the proportion of visitors to Norway that arrive by each mode of transport.

The figure demonstrates that the majority of visitors access Norway through the international

ferry ports and airports, as opposed to by rail and road across the border. Those that do arrive

by land based transport tend to originate from Sweden. The high ferry share is owing to the

impact of tourist trips to coastal towns and the scenic fjords, with a large number of passengers

from Germany and Denmark.

Figure 2.17 – Proportion of international tourists by arrival mode (2009)8

HSR is unlikely to have much impact on the ferry market share, but the proposed connections to

Stockholm and Gothenburg may shift surface transport share to HSR. There is currently only a

small proportion of visitors from Sweden arriving by air (see Figure 2.18), suggesting there is

limited demand from mode shift to HSR from air in Sweden.

Figure 2.18 – Proportion of Swedish tourists by arrival mode (2009)9

From this study of the existing tourism related travel market it can be concluded that:

Most popular ski resorts and natural attractions are located in remote areas away from the

main corridors which drive demand for travel;

Some of the most popular ticketed attractions are located in major urban centres and tourism

may attract further demand to these centres;

8 Source: Transportøkonomick Institutt, (2009), Gjesteundersøkelsen

9 Source: Transportøkonomick Institutt, (2009), Gjesteundersøkelsen

0% 20% 40% 60% 80% 100%

Car

Train/Coach

Ferry

Air

0% 20% 40% 60% 80% 100%

Car

Train/Coach

Ferry

Air



The majority of overnight stays by domestic and foreign visitors are made along the Bergen

and Trondheim corridors; and

Existing tourists arrive mainly by ferry and air. Swedish tourists, unsurprisingly, use surface

transport, with a low air arrival share.

2.2.5 Size of Existing Travel Market: Conclusions

This section of the report has examined current patterns of long-distance travel between the

major Norwegian cities and travel corridors, using data from the NTM5 model, adjusted with

Avinor airport-to-airport passenger data and NSB ticket sales data. Demographic and tourism

data has been obtained from Statistics Norway.

Key conclusions are:

Population tends to concentrated in the south-east of Norway and along the coast. There are

large, sparsely populated areas internally resulting in wide spaces between the main areas of

population demand. Therefore, development of HSR routes should generally focus on serving

end-to-end markets, with the exception of routes to the south-east of Norway;

Income levels are highest around the major cities, and in the south-east as a whole. To

compete with air travel – and provide the best commercial case for HSR – accessibility to

areas outside city centres may be important;

In terms of overall volumes of travel, Oslo-Bergen is significantly larger than other corridors,

followed by Oslo-Trondheim and Oslo-Stavanger. International experience suggests that

high volumes of travel generally produce the best economic / financial case for HSR routes,

suggesting that the Oslo-Bergen and Oslo-Trondheim corridors are most important;

Domestic air travel dominates long-distance business trips, due to its speed and frequency

compared with other modes. The mode share is highest on the longest distance routes such

as Oslo-Trondheim. Any HSR proposal will need to offer an attractive alternative to air to

achieve significant modal shift;

For leisure trips demand is more evenly spread between car and air compared with business.

Leisure passengers are more likely to drive than business passengers, due to costs, lower

value of time and the ability to raise private vehicle occupancy. Hence, HSR proposals will

need to balance competitiveness with air for business travel with competitiveness with car –

and price sensitivity – for leisure travel;

City-to-city travel is more likely to be by air and rail than travel between wider regions. This is

because of better road accessibility to urban hinterlands and reduced public transport

options. If limited stops are provided on HSR routes, this may restrict its ability to abstract

from wider regional flows by car;

Classic rail has low mode share for business travel (10-20%) but carries more leisure

passengers (20-30%). The Oslo-Bergen route attracts the highest leisure share to classic rail

possibly because of the scenic nature of the journey – this may inhibit shift to HSR along the

same corridor if a similar scenic nature is not achieved on any new alignment; and

The tourism market may have some impacts on demand, although the most popular

attractions tend to be away from cities. The seasonal nature of the tourism in Norway leads

to variations in demand, and it may be difficult to attract this market to HSR beyond the core

city-to-city markets.



2.3 Comparison of Services

2.3.1 Introduction

The following section presents a review of the current level of service along the six transport

corridors in Norway, for the purpose of comparing the travel opportunities for each mode of public

transport. The parameters in this section have been gathered from a desk study of transport

operators‟ websites. The modes considered are rail, air and coach, as well as ferry for the

Bergen – Stavanger corridor. For each mode the distance, fastest journey time, a range of

possible fares (where available) and service frequency is given.

2.3.2 Classic Rail

Classic rail services in Norway are operated by NSB, with the exception of the Airport Express

Train, operated by Flytoget, which connects Oslo with its main airport, Gardermoen. The NSB

network is fairly extensive in southern Norway, although due to the challenging topography, with

large mountainous and forested areas, as well as several lakes and fjords, rail travel is relatively

slow due to large distances of single track rail with large curvature. The following sections and

tables present the level of service from Oslo to key destinations on each corridor. Key

destinations are based on potential station locations for the proposed HSR services.

Oslo – Trondheim

The Dovre Line to Trondheim is served by four long-distance trains per day to Trondheim, one of

which is a sleeper train. There are also local stopping services at each end of the line, serving

the suburbs of Oslo and Trondheim, as well as the airport express services to Gardermoen and

regional services on the line from Skien to Lillehammer via Oslo. Gjøvik is served by a regional

service operating on a separate line from Oslo.

Regional and long-distance services have been accelerated between Oslo Central Station and

Eidsvoll, just to the north of Gardermoen Airport, with the opening of the Gardermoen Line in

1998. The line allowed for separation of local and regional services, reducing the possibility of

delays. Also the maximum speed of 210 kph is significantly higher than the rest of the network

and is the only high speed line in Norway.

Table 2.6 provides a summary of the level of service from Oslo to key stations en-route. For

Oslo to Oslo Gardermoen, figures for both NSB regional services and airport express services

have been shown.



Table 2.6 – Summary of rail level of service in Trondheim corridor (2010)10

Route Rail distance

(km)11

Fastest journey time (hours:mins)

Cheapest advanced fare (NOK)

Walk-up fare (NOK)

Services per day

Oslo – Gardermoen12

52 00:19 / 00:26 - 170 / 110 108 / 35

Oslo – Gjøvik 124 01:55 199 238 12

Oslo – Hamar 126 01:20 199 238 21

Oslo – Lillehammer 184 01:57 199 339 21

Oslo – Otta 297 03:26 199 536 5

Oslo – Trondheim 553 06:36 199 852 4

Oslo – Bergen

There are five services per day between Oslo and Bergen, including one sleeper train, providing

end-to-end travel and linking the villages and ski resorts along the route. On the line between

Oslo and Drammen, long-distance services heading towards Bergen share tracks with local,

regional and long-distance services heading towards Skien and Kristiansand, as well as airport

express trains from Gardermoen. At the opposite end of the Bergen route there are regular

commuter services between Voss and Bergen.

A new double track line is under construction between Oslo and Asker in order to separate local

and regional services on this very busy route, similar to the Gardermoen Line which has already

been completed to the east of Oslo. This will reduce delays caused by the high volume of

services all using the same tracks.

Table 2.7 below gives a summary of the level of service from Oslo to significant stations en-route

to Bergen.

Table 2.7 – Summary of rail level of service in Bergen corridor (2010)

Route Rail distance

(km)



Walk-up fare

(NOK)

Services per day

Oslo – Drammen 53 00:36 - 91 63

Oslo – Kongsberg 99 01:07 - 169 25

Oslo – Hønefoss 124 01:25 - 175 5

Oslo – Gol 208 02:48 199 373 5

Oslo – Geilo 253 03:31 199 459 5

Oslo – Voss 385 05:21 199 686 5

Oslo – Bergen 484 06:28 199 775 5

10 Sources: http://www.nsb.no/home/, http://www.flytoget.no/eng/

11 Source: JBV Network Statement 2011 http://www.comitato.com/V2/

12 Data for airport express train and NSB services



Oslo – Kristiansand – Stavanger

There are two regional services that head south west from Oslo; the long-distance service on the

Sørland line to Kristiansand and Stavanger, and services from Lillehammer via Oslo that serve

the Vestfold line which branches off at Drammen, passing through large towns such as

Tønsberg, Sandefjord and Larvik before terminating at Skien.

There are five long-distance services per day to Kristiansand, of which four continue on to

Stavanger, and there is a branch line serving Arendal.

Table 2.8 provides a summary of the level of service to key stations between Oslo and Stavanger

served by these routes.

Table 2.8 – Summary of rail level of service in Kristiansand-Stavanger corridor (2010)

Route Rail distance

(km)



Walk-up fare

(NOK)

Services per day

Oslo – Drammen 53 00:36 - 91 63

Oslo – Torp Airport 135 01:41 199 224 21

Oslo – Porsgrunn 190 02:34 199 300 22*

Oslo – Arendal 318 04:06 199 501 5*

Oslo – Kristiansand 365 04:25 199 631 5

Oslo – Stavanger 599 07:42 199 886 4

*These routes currently require an interchange

Oslo – Gothenburg

The Østfold Line links Oslo to the Swedish border near Kornsjø. There is an hourly service to

Halden, with three trains per day continuing on to Gothenburg. Between Oslo and Moss the

regional services share tracks with local Oslo commuter services. A new line is being planned

between Oslo and Ski with a line speed of approximately 200 kph, which will segregate local and

regional traffic, increasing line capacity and reducing journey times to long-distance destinations.

Table 2.9 summarises the level of service from Oslo to key regional destinations on the Østfold

Line and onto Gothenburg.

Table 2.9 – Summary of rail level of service in Gothenburg corridor (2010)

Route Rail distance

(km)



Walk-up fare

(NOK)

Services per day

Oslo – Ski 24 00:22 - 60 85

Oslo – Moss 60 00:41 - 123 41

Oslo – Fredrikstad 94 01:05 - 182 21

Oslo – Sarpsborg 109 01:19 - 182 21

Oslo – Halden 137 01:43 199 231 21

Oslo – Gothenburg 349 03:54 199 484 3



Oslo – Stockholm

NSB provide five long-distance services along the Kongsvinger line to Charlottenberg, which is

located in Sweden near to the border with Norway. From here the service is operated by the

Swedish operator SJ to Karlstad, with two direct services a day continuing on to Stockholm. At

other times of day there are connecting trains from Karlstad. The long-distance services share

tracks with local trains to Kongsvinger, as well as Dovre Line services and the Airport Express as

far as Lillestrøm.

Table 2.10 gives the level of service from Oslo to key stations along the route to Stockholm.

Table 2.10 – Summary of rail level of service in Stockholm corridor (2010)13

Route Rail distance

(km)



Walk-up fare

(NOK)

Services per day

Oslo – Lillestrøm 21 00:11 - 60 100

Oslo – Kongsvinger 100 01:08 - 193 11

Oslo – Karlstad 327 02:56 199 244 5

Oslo – Stockholm 572 06:05 214 494 414

Local Services

Table 2.11 below provides a summary of the services operating on the suburban routes around

the key cities in Norway. It can be seen that these services operate at a far higher frequency

than the long distance services.

Table 2.11 – Summary of local rail services in Norway

City Route Termini Frequency

Oslo 300 Skøyen Jaren 1 train per hour (tph) to Jaren, 1 train every 2 hours to Gjøvik

Oslo 400 Asker Lillestrøm 2tph

Oslo 440 Drammen Dal 1tph

Oslo 450 Kongsberg Eidsvoll 1tph

Oslo 460 Skøyen Kongsvinger 1tph to Ǻrnes, approx. 11 trains per day to Kongsvinger

Oslo 500 Skøyen Ski 2tph

Oslo 550 Spikkestad Moss 1tph

Oslo 560 Skøyen Mysen 1tph

Trondheim 26 Lerkendal Steinkjer 1tph, 3 trains per day serving Trondheim to Røros

Bergen 45 Bergen Myrdal 2tph to Arna, 1 train every 2 hours to Voss, 4 trains per day to Myrdal

Stavanger 59 Stavanger Egersund 4tph to Sandnes, 2tph to Nærbø, 1tph to Egersund

13 Additional source: http://www.sj.se/sj/jsp/polopoly.jsp?d=10&l=en

14 2 services require interchange at Karlstad



In conclusion, there is a fairly extensive existing rail network in Norway, serving all of the major

transport corridors. For journeys of approximately 100 km or less, there is a high frequency of

service, especially in the areas surrounding Oslo, and to some extent, the other main cities. The

rail network surrounding Oslo is subject to improvements in the near future, such as double-

tracking, to further increase capacity. For long-distance journeys, services are far more

infrequent and journey times are long, especially when compared with air travel. Fares for long-

distance journeys can be very cheap if booked far in advance.

2.3.3 Coach

Long-haul coach services in Norway are operated by several private companies, most of which

operate under the overarching brand of Nor-way Bussekspress. The services provide a public

transport alternative where there is no direct rail service available, such as between Bergen and

Stavanger, as well as competing with rail on some routes, particularly in western Norway. As

with the rail network, road travel in Norway becomes slower with greater distance from Oslo, due

to the challenging topography and weather conditions, hence long-distance journeys are

particularly slow. On many routes there is no direct coach service and one or sometimes two

interchanges have to be made. In these cases the fastest journey time presented includes

interchange time.

Oslo – Trondheim

There is a frequent coach service between Oslo and Gardermoen Airport. There are also some

express coaches to regional destinations. Coach travel to Trondheim and further north is less

frequent and often requires interchange. Table 2.12 presents a summary of the coach service on

the Trondheim corridor.

Table 2.12 – Summary of coach level of service in Trondheim corridor (2010)15

Route Road distance

(km)16


Minimum fare

(NOK)

Maximum fare

(NOK)

Services per day

Oslo – Oslo Gardermoen 49 00:45 140 200 53

Oslo – Hamar 128 02:00 150 150 1

Oslo – Lillehammer 184 02:50 150 315 6

Oslo – Otta 295 05:05 282 460 5

Oslo – Trondheim 496 08:30 199 850 4*

*Some require interchange

15 Source: http://www.nor-way.no/?lang=en_GB

16 Source: http://www.vegvesen.no/en/Traffic/Planning+your+trip/Route+planner



Oslo – Bergen

For long-distance travel towards Bergen, interchange is often required to reach the final

destination, although there are a limited number of direct coach services each day to

intermediate destinations, such as Geilo and Gol, shown in the table below. Table 2.13 gives a

summary of the coach service on the Bergen corridor.

Table 2.13 – Summary of coach level of service in Bergen corridor (2010)

Route Road distance

(km)


Minimum fare

(NOK)

Maximum fare

(NOK)

Services per day

Oslo – Gol 191 03:30 355 355 6*

Oslo – Geilo 243 04:25 420 420 4*

Oslo – Voss 385 08:00 690 746 4*

Oslo – Bergen 484 10:25 509 805 4*

*Some or all require interchange

Oslo – Kristiansand – Stavanger

There is a more comprehensive coach service to towns and cities along the Oslo – Stavanger

corridor compared with Oslo to Bergen and Trondheim, as shown in Table 2.14 below.

Table 2.14 – Summary of coach level of service in Kristiansand-Stavanger corridor (2010)

Route Road distance

(km)


Minimum fare

(NOK)

Maximum fare

(NOK)

Services per day

Oslo – Torp Airport 118 03:30 465 535 8*

Oslo – Porsgrunn 141 02:25 310 310 16

Oslo – Arendal 261 03:50 350 350 12


Oslo – Stavanger 540 09:10 219 860 6*

*Some require interchange

Bergen – Stavanger

The Bergen – Stavanger corridor is the best served by coach, as there is no rail service in this

region. Frequent services are provided, although journey times are long, owing to the need to

cross several fjords and mountainous areas en-route. The level of service is summarised in

Table 2.15.

Table 2.15 – Summary of coach level of service in Bergen-Stavanger corridor (2010)

Route Road distance

(km)


Minimum fare

(NOK)

Maximum fare

(NOK)

Services per day

Bergen – Stord (Leirvik) 83 02:10 220 220 15

Bergen – Haugesund 139 03:15 320 320 12

Haugesund – Stavanger 89 02:30 240 240 10

Bergen – Stavanger 211 05:00 490 490 13



Oslo – Gothenburg

Coaches between Oslo and Gothenburg are operated by the Swedish company Swebus. They

offer up to five services a day, with two stopping at Sarpsborg. There is also a regular coach

service operated by Nettbuss which runs between Oslo and Halden. Key parameters are shown

in Table 2.16 below.

Table 2.16 – Summary of coach level of service in Gothenburg corridor (2010)17

Route Road distance

(km)18


Minimum fare

(NOK)

Maximum fare

(NOK)

Services per day

19

Oslo – Moss 58 00:50 125 125 17

Oslo – Sarpsborg 89 01:05 57 175 21

Oslo – Halden 116 02:10 190 190 7

Oslo – Gothenburg 293 03:35 45 243 5

Oslo – Stockholm

Services between Oslo and Stockholm are also operated by Swebus, with four services per day

between Oslo and Karlstad, three of which continue on to Stockholm. There is also a service

operated to Stockholm by “bus4you”. The level of service is shown in Table 2.17.

Table 2.17 – Summary of coach level of service in Stockholm corridor (2010)

Route Road distance

(km)


Minimum fare

(NOK)20

Maximum fare

(NOK)

Services per day

Oslo – Karlstad 219 03:05 42 207 4

Oslo – Stockholm 523 07:30 77 455 5

In conclusion, coaches play an important role in Norwegian public transport, in particular serving

routes that are not well served by other modes of transport. Coach travel is a cheap alternative

for those who cannot afford to run a car. However, on long-distance routes which are well served

by air, service frequencies are low and journey times are far slower. For the intercity markets

that any potential HSR is likely to serve, coaches are unlikely to offer direct competition, although

they will continue to play an important role serving more rural routes and accessing regional

airports from city centres.

2.3.4 Ferry

Fast ferries operate along the west coast, across fjords and to islands where it is quicker to follow

the waterways than the roads, and some small islands are served by water buses. The only ferry

route which is relevant to long-distance travel along the HSR corridors considered is the

Flaggruten, operated by Tide. This service connects Bergen and Stavanger, a route which is not

served by classic rail.

Table 2.18 summarises the level of service to the main destinations served by the Flaggruten.

17 Source: http://www.swebus.se/SwebusExpress_com/, http://www.nettbuss.no

18 Source: http://www.rac.co.uk/route-planner/

19 Number of services varies depending on day of the week

20 Based upon an exchange rate of 1 SEK = 0.88 NOK



Table 2.18 – Summary of ferry level of service in Bergen-Stavanger corridor (2010)21

Route Distance (km)


Walk-up fare (NOK)

Services per day

Bergen –- Stord / Leirvik 60 02:10 310 4

Bergen – Haugesund 100 03:10 510 2

Haugesund – Stavanger 60 01:20 310 4

Bergen – Stavanger 160 04:30 730 2

The table shows that ferry travel offers a viable alternative to road travel on this corridor, with

journey times similar to those achieved by coach. However, for the city-to-city market between

Bergen and Stavanger, air travel is vastly quicker, as described below.

2.3.5 Air

Because of the often slow road and rail networks in northern and western Norway there is a high

demand for domestic air services for intercity and long-distance travel. The primary airports are

served by jets from Scandinavian Airlines and Norwegian, while the smaller regional airports

located north of Trondheim are generally served by smaller aircraft operated by Widerøe.

Service on Key Routes

Table 2.19 below presents the level of service for key air routes from Oslo and between Bergen

and Stavanger on a typical weekday.

Table 2.19 – Summary of air level of service on key routes within Norway and to Sweden (2010)22

Route Approx. ‘crow flies’

distance (km)

Flight time (hours:mins)

Minimum fare (NOK)

Maximum fare (NOK)

Services per day

Oslo – Trondheim 390 00:55 299 1990 25

Oslo – Bergen 310 00:50 299 1990 28


Oslo – Stavanger 300 00:50 299 1990 23

Bergen – Stavanger 160 00:35 359 1717 14

Bergen – Haugesund 100 00:30 361 1443 2

Oslo – Gothenburg 250 00:55 460 2502 8

Oslo – Stockholm 420 01:00 299 2227 17

The table shows that for the main long-distance routes, there are a large number of flights per

day. For shorter routes, such as Oslo-Kristiansand and Oslo-Gothenburg there are fewer flights,

presumably because air has less of an advantage over other modes of travel in terms of journey

time savings, and hence there is less demand. There are a large number of flights from Bergen

to Stavanger, however. This is possibly due to the combination of a lack of rail service between

the two cities, and car travel requiring several transfers to ferry en route to cross fjords.

21 Source: http://eng.tide.no/Default.aspx?pageid=1055

22 Sources: http://www.wideroe.no/?language=en, http://www.norwegian.com/en/,

http://www.flysas.com/en/uk/?vst=true



Access to Airports and Airport Handling Times

As is to be expected, air journeys provide the fastest mode of transport for long-distance journeys

from Oslo to the other major cities in Norway. It should be noted however that air journeys

generally have longer access times from city centres and check-in time should also be

considered.

As in most countries, rail stations and coach terminals in Norway are usually located in towns

and city centres, often adjacent to each other and near stops for local bus routes and light rail

systems, allowing for easy interchange between modes.

In contrast, the airports in Norway are located some distance from the town / city centres. All

Norwegian airports can be reached by car and, in many instances, public transport. Table 2.20

gives an overview of the quality of public transport to / from the major airports serving the

relevant corridors, in terms of access time, cost and frequency.

Table 2.20 – Access to key airports in Norway and Sweden (2010)23

Airport Distance from city centre (km)

Mode Time Cost Frequency (per hr)

Oslo Gardermoen 46 Train 00:19 170 8

Coach 00:45 140 53

Trondheim Værnes 33 Train 00:35 64 1

Coach 00:35 100 4

Bergen Flesland 12 Coach 00:25 90 4

Kristiansand Kjevik 16 Coach 00:25 120 1

Stavanger Sola 11 Coach 00:25 90 3

Haugesund (Karmøy) 14 Coach 00:25 70 <124

Gothenburg Landvetter 20 Coach 00:30 70 3

Stockholm Arlanda 37 Train 00:20 211 10

Coach 00:35 65 10

The table demonstrates that the airports are all located within 50km of the city centres and

access times are all fairly similar, with the larger airports located further from the city centre,

namely Oslo and Stockholm, having a faster and more regular service.

In addition the check-in time can vary depending on the airport and the type of flight. For the

purpose of this work it is assumed that attendance time at the airport will amount to one hour for

domestic flights and 1.5 hours for international flights, as recommended by Avinor25

. This will

enable a fairer comparison between air travel and other modes.

For the comparison between air travel and other modes below, the parameters for air travel have

taken into account travel to and from the airport, as well as an assumption for airport check-in

time.

23 Sources: http://www.nsb.no/home/, http://www.flybussen.no/,

http://www.flygbussarna.se/Default.aspx?lang=EN, http://www.arlandaexpress.com/start.aspx 24

Coach leaves 20mins after each flight arrives 25

http://www.avinor.no/en/avinor/baggageandcheckin/30_Check-in



2.3.6 Comparison

This section compares the level of service on each corridor offered by each mode.

Service Frequency

Table 2.21 compares the service frequencies for end-to-end journeys on each corridor. Air

journeys are the most frequent with over 20 departures per day for the main domestic routes and

Stockholm. Rail and coach journey frequencies are much lower but roughly similar. An exception

is Bergen to Stavanger, where there is no rail route, so coach journeys are more frequent to meet

the travel demand.

Table 2.21 – Summary of 2010 service frequency on key corridors

Route Air Rail Coach

Oslo – Trondheim 25 4 2

Oslo – Bergen 28 5 4

Oslo – Kristiansand 8 5 18

Oslo – Stavanger 23 4 6

Bergen – Stavanger 14 0 13

Oslo – Gothenburg 8 3 11

Oslo – Stockholm 17 4 5

Journey Times

Air is the fastest mode of transport for long-distance journeys from Oslo to the other major cities

in Norway and Sweden, even when access and airport handling times are taken into account.

Existing rail is the next fastest mode, followed by coach travel. In two examples (Gothenburg

and Kristiansand), the journey time is not significantly different between rail and road; however

others such as Trondheim and Bergen show that rail is vastly quicker than coach travel. End-to-

end journey times between Oslo and Gothenburg by air are not significantly quicker than rail or

coach travel. This could explain the dominance of road travel along this corridor, as the

advantage of convenience and lower cost of driving, especially for group travel, overrides any

small journey time savings by air. Journey times are summarised in Table 2.22 below.

Table 2.22 – Summary of 2010 fastest journey times on key corridors (hr:min)


Oslo – Trondheim 02:49 06:36 08:30

Oslo – Bergen 02:34 06:28 10:25

Oslo – Kristiansand 02:29 04:25 05:30

Oslo – Stavanger 02:34 07:42 09:10

Bergen – Stavanger 02:25 N/A 05:00

Oslo – Gothenburg 03:14 03:54 03:35

Oslo – Stockholm 03:09 06:05 07:30

Fares

The cost of air journeys varies greatly, depending on the popularity of the route, the time of day

and how far in advance the ticket is booked. Coach and rail fares are set for each route,



however there is variation in rail fares as cheaper advance tickets are available, while coach

fares vary depending on the route taken. Table 2.23 gives a summary of the cheapest and most

expensive fares available for each transport mode.

Table 2.23 – Summary of 2010 range of fares on key corridors (NOK)


Lower limit

Upper limit

Lower limit

Upper limit

Lower limit

Upper limit

Oslo – Trondheim 299 1,990 199 856 495 850

Oslo – Bergen 299 1,990 199 788 680 805

Oslo – Kristiansand 259 1,931 199 636 350 350

Oslo – Stavanger 299 1,990 199 886 860 860

Bergen – Stavanger 359 1,717 N/A N/A 320 320

Oslo – Gothenburg 460 2,502 199 484 45 243

Oslo – Stockholm 299 2,227 214 562 77 455

If purchased on the day, rail fares in Norway are set depending on length of journey. NSB

Regional Trains offer a limited number of „Minipris‟ (advance) tickets on the majority of their

routes, costing NOK 199, 299, and 399. Generous discounts are currently offered on Norwegian

trains, including 90% discount for military in uniform, 25-40% student discount and 50% senior

citizen discount. There is, however, no discount for group bookings.

Coach journeys with Nor-way Bussekspress have a set fare depending on the journey distance,

with a 10-40 NOK discount available for online booking (not available on the day of journey).

There is also a variation in fares depending on the route taken. Swebus, who operate the

Stockholm and Gothenburg coaches, do not have a set price. Fares do not vary greatly around

the mean price, but can be higher the closer to the day the journey is booked and the more

popular the travel time/date.

Flights tend to increase in price the closer to the travel date that the ticket is booked and fares

are higher at peak times (weekends, public holidays). Norwegian Air offer cheaper fares for

customers booking in advance who do not require a flexible (refundable) ticket, especially at off-

peak times.

Station / Terminal Facilities

A detailed discussion of station and terminal facilities is contained within the report for Subject 4

– Location and Services of Stations / Terminals.

2.3.7 Other Factors

Weather Conditions

The Norwegian transport network is regularly affected by adverse weather due to the harsh

climate, particularly in the winter. The long-distance intercity rail and road routes traverse

mountain areas which can lengthen journey times when the weather is poor. On the road

network in particular, some mountain passes are subject to severe snowstorm problems in the

winter, so often they have to be closed, or cars have to drive behind a snowplough in a column

formation. The weather contributes greatly towards the passenger choice of transport mode,

causing a variation in the seasonal demand on key routes.



Ability to Work

A key consideration for business travellers is whether they are able to work while travelling. Rail

and coach services have the advantage of being able to provide wi-fi and mobile phone reception

during the journey. Airlines are often unable to offer this service except in departure lounges.

Both rail and air modes offer varying degrees of service quality depending on whether standard

or premium (first class) tickets are purchased. NSB do not sell first class tickets but offer a

premium service, known as “NSB Komfort”, which is available for a supplement of 90 NOK on all

long-distance routes, regardless of the length of journey. This service offers a separate

compartment, complimentary tea and coffee, newspapers and access to a power socket for

laptops26

.

2.3.8 Service Comparison Conclusions

The classic rail services in Norway are a combination of local, regional and long-distance

services, with local and regional services operating at a far greater frequency. On each

corridor there are a small number of long-distance rail services linking Oslo with the other

main cities in Norway, namely Bergen, Trondheim, Kristiansand and Stavanger, and

Stockholm and Gothenburg in Sweden. These services are very infrequent when compared

with the number of air services, and the journey times are far slower when compared with air

travel. HSR is likely to need to achieve a far higher level of journey frequency – as well as

improved journey times – to abstract from air;

Coach services are primarily designed to serve popular routes not well served by rail, for

example, Bergen to Stavanger. On other routes well served by air and / or rail, coach

services are very infrequent. Journey times are very slow when compared with air and

interchange is often required between coach services. However, they provide reasonable

competition on the Oslo – Kristiansand corridor, where HSR could be expected to abstract

some demand;

A consideration that must be made with air travel is access to the airport, which results in

added time and cost to the overall journey. However, even when these are taken into

account, air compares favourably with coach and rail for journeys over 200km. Similar or

better accessibility to HSR stations needs to be provided; and

Air fares are considerably more expensive than rail and coach if bought on the day or for

journeys at peak times, especially if a flexible ticket is required. However, if bought in

advance for off-peak journeys, air fares can be in a similar range to comparable rail and

coach fares. HSR services need to offer a full range of fares to maximise commercial return

and compete effectively with both rail and air on price and journey time, respectively.

26 Source: www.nsb.no



2.4 International Benchmarking

This section compares the current HSR services in other European countries, namely Sweden,

France, Germany, Spain and the UK. Sweden was chosen for this study as it has a similar

geography and population density to Norway. France, Germany and Spain were considered as

they already have well developed and successful HSR networks; for the UK Atkins was able to

draw on extensive local knowledge.

2.4.1 HSR Demand

Size of Markets

Table 2.24 shows the size of HSR markets in 2008 for selected European countries. Note that

demand in the UK is for Eurostar only and does not include domestic high speed travel, which

commenced in 2009. The table shows that France currently has the largest demand for HSR,

followed by Germany. Spain has the next largest market for HSR, which is likely to growth

significantly in the coming decade as it is in the process of expanding its network. The mean

distance travelled in Germany is lower than France and Spain due to the very high population

density of the country. The UK and Sweden have smaller markets for HSR due to the relatively

small size of the networks.

Table 2.24 – Size of HSR markets in other European countries (2008)27

Country Operator Passengers per year

(thousands)

Passenger km per year

(millions)

Mean distance travelled (km)

Germany DB 74,700 23,333 312

Spain RENFE 22,955 10,490 457

France SNCF 116,054 52,564 453

UK Eurostar 9,100 993 109

Sweden SJ 8,764 2,992 341

In comparison with the markets for Germany and France described above, the market for travel

in Norway is relatively small. For example, the total passenger journeys made by air, including

transfers, in the 6 main corridors based on air ticket count data is just under 6 million per year

(see Figure 2.10), compared with 75 million HSR passenger journeys in Germany and 116 million

in France. Therefore even if HSR abstracted all air demand on the key corridors in Norway, as

well as a proportion of long-distance rail and car journeys, the market would be less than 10% of

the size of that in Germany and France. However, the market for HSR would be in the same

order of magnitude as that in Sweden, the country with more similar characteristics to Norway,

such as population size and distribution.

Market Share

New HSR routes have proved very successful in abstracting demand from air travel. Table 2.25

summarises the market share on key European routes in 2008. On some shorter routes where

HSR from city centre to city centre has a faster overall journey time than air travel, such as Paris

to Brussels, air demand has almost diminished completely. On slower HSR routes, such as

between Paris and Amsterdam, and Stockholm and Gothenburg, the rail market share is lower.

It should be noted that the Madrid-Barcelona line was fully completed in 2008. Therefore it is

likely the impact of HSR on the travel markets had not yet taken effect.

27 Source: http://www.uic.org/IMG/pdf/50-2008_hs_commercialtraffic.pdf



Table 2.25 – Market share of HSR and air on key routes in other European countries (2008)28

Route Distance (km)

Journey Time

(hr:min)

Average Speed (kph)

Rail Share Air Share

Madrid – Barcelona 630 02:40 229 50% 50%

Madrid – Seville 471 02:20 195 83% 17%

Paris – Amsterdam 450 04:00 113 45% 55%

Paris – Brussels 310 01:20 219 95% 5%

Paris – London 444 02:15 197 81% 19%

Paris – Lyon 430 02:00 215 90% 10%

Stockholm – Gothenburg 455 03:00 152 62% 38%

2.4.2 Quality of Service

The following section describes the level of service provided on HSR routes in the European

countries studied.

Sweden

In Sweden the X2000, Intercity and some regional services, as well as the Arlanda Airport

Express, all have a maximum speed of 200 kph, which is reached on certain sections of track.

Long-distance destinations served by these trains include Stockholm, Gothenburg and Malmö.

The X2000 service is the quickest long-distance service, stopping at the fewest stations on route.

Table 2.26 summarises the key routes served by HSR.

Table 2.26 – Summary of level of service on HSR in Sweden (2010)

Route Distance by rail (km)

Fastest Journey

Time (hrs:mins)

Cheapest advanced

fare (NOK)

29

Walk-up fare (NOK)

Max daily freq of

fast services

Stockholm – Copenhagen 661 05:02 282 1,082 6

Stockholm – Gothenburg 453 02:52 128 1,092 16

Stockholm – Arlanda Airport 39 00:20 N/A 211 79

France

The French TGV high speed train has proved very successful since the first high speed line was

opened between Paris and Lyon in 1981; patronage has continued to increase as the network

has gradually expanded to other areas of France and linked to high speed lines in other

countries. The TGV services run on a combination of dedicated HSR lines at speeds of up to

300 kph and at lower speeds on upgraded classic rail lines.

Table 2.27 provides a summary of journey times, distances and single fares to major stations

served by HSR lines from Paris.

28 Source: De Rus, G., (2008), The Economic Effects of HSR Investment, International Transport Forum

29 Based upon an exchange rate of 1 SEK = 0.88 NOK



Table 2.27 – Summary of level of service on HSR in France (2010)30


31

Fastest Journey

Time (hrs:mins)

Cheapest advanced

fare (NOK)

32

Walk-up fare (NOK)

Max daily freq of

fast services

Paris Lyon – Lyon Part Dieu 429 01:57 202 629 26

Paris Nord – Brussels Midi 314 01:20 226 792 30

Paris Lyon – Marseille St Charles

750 03:03 202 792 19

Paris Nord – London St Pancras

495 02:15 374 1,344 16

Paris Est – Frankfurt 586 03:49 316 859 5

Paris Est – Cologne 473 03:14 235 851 4

Germany

Like France, Germany has an extensive HSR network, using a combination of upgraded classic

rail, with speeds of up to 250 kph, and sections of new lines, with a line speed of 300 kph. The

German high speed network is better integrated with the classic rail network than France,

although there is less overall length of segregated high speed lines. This, combined with more

station stops due to the higher density of population, results in longer journey times overall on the

main routes. High speed services are known as Intercity Express (ICE) and are operated by

Deutsch Bahn, the German railway company.

Table 2.28 – Summary of level of service on HSR in Germany (2010)33


Fastest Journey

Time (hrs:mins)


Walk-up fare (NOK)

Max daily freq of

fast services

Cologne – Frankfurt 186 01:02 235 518 29

Cologne – Stuttgart 368 02:13 235 794 8

Cologne – Berlin 551 04:20 235 883 15

Frankfurt – Berlin 593 03:36 235 915 13

Frankfurt – Munich 429 03:10 235 737 17

Spain

HSR in Spain has grown rapidly in recent years, with large investment into new infrastructure.

Journey times between major cities in Spain are now some of the fastest in the world and have

an exceptional punctuality record (passengers are given a full refund if the service is over five

minutes late on the Madrid – Seville route). The high speed lines have been constructed to

standard gauge, as opposed to the Spanish wide gauge, in order to link to other European

networks, and a line from Barcelona to Perpignan in France is due to be completed in 2012. The

30 Sources: http://www.raileurope.co.uk/, http://www.tgv-europe.com/en/home/

31 Source: http://www.trainweb.org/tgvpages/jpg/frdistancemap.jpg

32 Based on exchange rate of 1 Euro = 8.1 NOK

33 Source: http://www.bahn.com/i/view/GBR/en/index.shtml



high speed service in Spain is known as Alta Velocidad Española (AVE) and is operated by the

Spanish state operator RENFE.

Table 2.29 – Summary of level of service on HSR in Spain (2010)34


Fastest Journey

Time (hrs:mins)


Walk-up fare (NOK)

Max daily freq of

fast services

Madrid – Barcelona 651 02:38 437 1,102 18

Madrid – Seville 472 02:20 267 656 22

Madrid – Malaga 513 02:25 275 697 12

Madrid – Valladolid 180 00:56 113 284 13

UK

In the UK there is currently one dedicated HSR line, known as High Speed 1, which links London

to the Channel Tunnel, enabling services to run to continental Europe at speeds of up to 300 kph.

International services to Paris and Brussels on this route are operated by Eurostar. Other

operators, such as Deutsche Bahn, have expressed an interest in running services from London

to other European destinations such as Amsterdam, Rotterdam and Frankfurt in the future.

In December 2009, domestic services began running on High Speed 1 from London St Pancras

to Ebbsfleet International or Ashford International before transferring to classic rail to reach

destinations in the south-east of England. Domestic services are permitted to run at speeds of

up to 225 kph on High Speed 1 and up to 160 kph on classic rail.

There are also four other main line routes which operate at speeds of up to 200 kph. Attempts

have been made to increase line speeds on classic rail to 225 kph but currently top speeds are

limited to 200 kph due to the lack of in-cab signalling, despite the higher potential speed of many

of the trains.

Table 2.30 provides a summary of journey times, distances and single fares to major stations

served by HSR lines from London.

34 Source: http://www.renfe.com/



Table 2.30 – Summary of level of service on HSR in the UK (2010)35


Fastest Journey

Time (hrs:mins)

Cheapest advanced

fare (NOK)

36

Walk-up fare (NOK)

Max daily freq of

fast services

London Euston – Birmingham New St

182 01:22 67 393 53

London Euston – Manchester Piccadilly

304 02:07 106 626 45

London Kings Cross – Newcastle

432 02:44 130 989 30

London St Pancras – Ashford 97 00:36 N/A 255 35

London St Pancras – Paris Nord

495 02:15 374 1344 16

London St Pancras – Brussels Midi

376 01:51 374 1344 10

2.4.3 Station Locations & Quality

Generally across Europe high speed trains tend to only stop at major stations en-route. These

stations are usually located in or near to large cities, and interchange at these is then possible in

order to reach smaller „feeder‟ stations.

The location of rail stations differs depending on the town/city. Some, such as London St

Pancras and Paris Gare de Nord are located right in the heart of the city and thus offer a very

competitive service to air travel when considering the reduced access travel time, check-in time

and time spent waiting for luggage. In countries such as France, high speed trains use existing

tracks and stations which are part of the classic rail network within urban areas.

Others stations are located on the outskirts of cities, often allowing for faster interchange with

other routes, easy access from the motorway or to serve an airport, with substantial parking

facilities. The advantage of these „parkway‟ style stations is that they allow for reduced journey

times by avoiding urban areas where fast line speeds are not viable. Examples include Ebbsfleet

International near London and Gare de Saint-Exupéry near Lyon. These stations often require a

further connection to reach the town centre. For this reason these types of station have generally

proved far less popular due to a lack of onward public transport connectivity to the nearby towns

and cities.

Further discussion of HSR station locations and facilities is contained within the report for Subject

4 – Location and Services of Stations / Terminals.

2.4.4 International Benchmarking Conclusions

Germany and France have well established HSR markets, with tens of millions of travellers

per year. On routes where HSR has been introduced, the market share for air has almost

completely diminished. The size of the HSR markets in countries such as France and

Germany are vastly larger than the likely market in Norway, based on the demand data

described in Section 2.2. The likely market for HSR, estimated from abstraction from air

travel and long-distance car and rail travel, is more similar to that in Sweden, a country of

similar geography and population to Norway.

35 Source: http://www.nationalrail.co.uk/

36 Based on exchange rate of £1 = 9.6 NOK



There is a mixture of approaches across Europe to improving long-distance rail travel, which

could be applied to Norway. In some countries, France and Spain in particular, HSR has

been rapidly developed with the construction of new lines, with further expansion planned for

the next decade. In countries such as the UK and Sweden, the focus of rail development has

been on upgrading existing classic rail lines, so the journey times are longer than those in

France and Spain.

The introduction of HSR in France, Germany and Spain has dramatically reduced rail journey

times between major cities. HSR services stop far more infrequently than classic rail, in order

to maintain low journey times and compete effectively with air travel. Stations tend to either

be located in the city centre or outside of cities in strategic locations, such as adjacent to a

motorway or airport, to provide onward connectivity.

HSR fares across Europe, when booked in advance, are not much higher than equivalent rail

fares in Norway, therefore the premium paid for a better quality of service and faster journey

time is very small. When compared with air fares in Norway, HSR fares are far cheaper.

2.5 Key Overall Conclusions

The size of the potential market for HSR in Norway is similar to that of Sweden, although much

smaller than the equivalent markets already established in countries such as France and

Germany. From experience in other European countries where HSR is already well established,

there has been almost total abstraction from air on routes served by HSR as rail journey times

have been dramatically reduced and major rail stations are located more conveniently than the

airports.

Business travel in Norway is dominated by air due to the relative speed and frequency of

services, and there is a higher value of time associated with these trips. Business travellers are

prepared to spend time accessing airports located outside city centres. Conversely, leisure travel

is more evenly spread between car, air and rail, and for travel within corridors car travel is

dominant, particularly between Oslo and Kristiansand, due to leisure travellers placing a higher

value on journey cost and the ability to travel as a group. Therefore, the key market for potential

HSR in Norway will be business travel, which is currently served by air, although HSR will look to

abstract from the leisure market on long distance routes.

Comparison of the level of service for individual modes of public transport indicates that air travel

provides the best service for city-to-city travel, both in terms of service frequency and journey

time, which explains the high market share. HSR services tend to stop less frequently than

classic rail but stations offer good connectivity with other modes of transport. Therefore any

potential HSR service in Norway would compete with city-to-city travel currently dominated by air,

rather than travel within corridors. In order to compete with air travel, HSR will need to offer a

competitive service, in terms of frequency, journey times, fares, accessibility and comfort.



3 Future ‘Do Minimum’ Travel Market 3.1 Introduction

This chapter sets out growth forecasts for long distance travel demand in Norway under Scenario

A, the Do Minimum scenario. The analysis is based on matrices for car, air, train and coach

journeys, as produced by the NTM5 model for 7 years ranging between 2010 (the base year),

and 2060.

The remaining subsections cover the following areas:

Overview of approach to future year forecasting;

Discussion of forecasts on key travel markets;

Comparison of the core forecasts with other forecasts available; and

Conclusions – implications for high speed rail development.

3.2 Overview of Future Year Forecasting Approach – NTM5 matrices

NTM5 defines „long distance‟ trips as those exceeding 100 kilometres. Demand is divided

between work-related trips and non-work trips, with further disaggregation of the latter into the

following 4 sub-categories: „Leisure‟, „Visits‟, „Other‟, and „Private‟. However, in order to avoid

overcomplicating the bespoke HSR mode choice modelling, the parameters and matrices used to

forecast scenarios C and D have only dual segmentation: that is, work (business) trips versus

non-work (all other) trips.

NTM5‟s future year matrices allow for the effects of rising population and economic activity, as

well as trips induced by committed improvements to the transport system. The future year

matrices supplied by TØI and used within the bespoke mode choice model, assume no change in

domestic air schedules, with 2006 levels of service assumed throughout. Discussions held

recently with the airlines suggest this is a reasonable assumption for the Do Minimum level of

service on this key mode, from which HSR is expected to abstract much of its demand.

With regard to classic rail, the National Transport Plan (NTP) 2010-2019 commits to a

programme of rail double-tracking, mainly on congested sections of the Intercity network in the

Greater Oslo region. Scenario A assumes that continuation of the current policies - including

further works in other regions - will allow long distance rail headways to be cut by 50% by the

early 2020s. By contrast, the future year matrices supplied by TØI for the appraisal of Scenarios

C and D, and used herein to present „Do Minimum‟ growth, assume that levels of service on all

modes reflect the networks and timetables expected in 2014. This implies only very modest

improvements to long distance classic rail services. However, analysis using NTM5 shows that

whilst the improved headways raise classic rail volumes by 9% in Scenario A – mainly by

abstracting car journeys - total demand volumes and air volumes are unaffected.

3.2.1 Economic and Demographic Demand Forecasts

In producing the future year Do Minimum matrices for each of the modes, NTM5 depends heavily

on forecasts of Norwegian population at county level.

Table 3.1 below shows the population projections for 2018 to 2060 that underlie the NTM5 matrix

outputs. These projections are from Statistics Norway‟s option „MMMM‟ (of June 2010) where

fertility, life expectancy, domestic mobility and net migration are set at their most likely values.

That is, these are the central case projections of population.

The rows in the table are ranked according to the overall rate of population growth.



Table 3.1 – Population projections index – Statistics Norway (SSB)

County 2010 2018 2020 2024 2030 2043 2060

Rogaland 100 112 115 120 129 146 166

Akershus 100 112 115 120 129 145 165

Oslo 100 113 117 122 130 146 165

Buskerud 100 109 111 115 122 136 153

Vest-Agder 100 108 111 115 122 135 152

Aust-Agder 100 108 110 114 121 134 150

Hordaland 100 109 111 115 122 134 150

Sør-Trøndelag 100 109 111 115 122 134 148

Østfold 100 107 109 113 119 131 146

Vestfold 100 107 109 113 119 130 145

Nord-Trøndelag 100 104 105 108 111 118 127

Hedmark 100 103 103 105 108 114 124

Møre og Ro. 100 104 105 107 110 116 124

Telemark 100 102 103 105 107 113 121

Troms 100 104 105 107 110 115 121

Oppland 100 102 103 104 107 112 120

Finnmark 100 100 100 101 101 104 109

Sogn og Fj. 100 100 100 101 102 104 108

Nordland 100 100 100 101 102 103 106

Total 100 108 110 114 119 131 145

It can be seen that nationally, population is forecast to rise by 45% by the end of the HSR

appraisal period in 2060. The lowest growth – just 6% – is found in Nordland in the far north,

whilst the maximum – around 65% – is forecast for Rogaland (including Stavanger, Sandnes,

and Haugesund) and the Oslo area (including the Akershus commuter belt).

The rapid population growth expected in Rogaland has positive implications for the potential of

the HSR proposals serving Stavanger (the Y-shaped option to Bergen and Stavanger, would also

serve Haugesund).

Apart from Rogaland (Stavanger), the other county populations associated with the main

Norwegian cities are projected to rise as follows: Vest-Agder (Kristiansand) 52%; Hordaland

(Bergen) 50%; and Sør-Trøndelag (Trondheim) 48%.

Figure 3.1 below shows the temporal profiles of population growth in the counties of most

importance to the HSR appraisal (the national profile, and that of Nordland county, are added for

reference).



Figure 3.1 – Population growth profiles (2010-2060)

Figure 3.1 shows that in the main HSR markets, rates of population growth actually decline

slowly through the HSR appraisal period. National population rises at 1% per annum between

2010 and 2020, falling to 0.6% per annum between 2043 and 2060 (each measured using a

compound annual growth rate). The maximum rate of annual growth is 1.8%, predicted for Oslo

between 2018 and 2020.

3.2.2 Standard Approach to Forecasting Demand in a Do Minimum Scenario

This section describes the method adopted for producing forecasts of future long-distance travel

demand, in the Do Minimum (no HSR) scenario. The mode choice model under development

requires future year matrices for each of the competing modes from which HSR may abstract,

principally air, car and (long-distance) classic rail.

Atkins‟ preferred approach to Do Minimum growth is set out in the next subsection, but first the

main alternative is described. This would have involved combining a set of forecasts for demand

drivers (e.g. GDP, population, rail and air fares, etc.) with corresponding „elasticities‟.

An elasticity measures the percentage change in demand (in this case, journeys by a particular

mode) to be expected when a particular demand driver changes by 1%. For example, if it is

known (or estimated) that the GDP elasticity for non-transfer leisure journeys on domestic

Norwegian flights is 2.0, and the long run trend increase in Norwegian GDP is 2.5% per annum,

then demand for such journeys will be expected to increase by 5% per annum, holding constant

all other demand drivers.

Ideally, sub-national socio-economic data would be used, in order to allow the appraisal of each

HSR corridor to incorporate spatial disparities in economic growth and population growth. This

would tend to benefit the corridors with the brightest market prospects, and penalise the HSR

business case elsewhere.

For fares effects, the application of an elasticity-based approach would need also to reflect

substitution of one mode for another. For example, long-distance rail demand might increase by

2% for every 1% increase in air fares. This requires the estimation of a system of equations,

unless fares across all modes change at the same rate. In fact, the NTM5 model assumes that

all monetary costs of travel are completely fixed (see below).

100

110

120

130

140

150

160

170

2010 2020 2030 2040 2050 2060

Population growth profiles

Rogaland Akershus

Oslo Vest-Agder

Hordaland Sør-Trøndelag

Nordland Total



The final influence on Do Minimum demand which would have required explicit consideration in

the alternative approach is planned („committed‟) changes in networks, and associated

improvements to „levels of service‟ for each mode. In the UK, the PDFH recommends use of a

„Generalised Journey Time‟ (GJT) approach for estimating the effects on demand of

improvements to rail timetables. This combines the effects of changes in station-to-station

journey times with allowance for the improvement in convenience when frequencies are

increased, or interchanges removed.

However, a simple single-mode approach based on GJT elasticities does not model where the

additional rail demand is drawn from. That is, there is no distinction between additional rail trips

abstracted from other modes, and „pure generation‟ (i.e. additional total travel induced by the rail

timetable improvement). For Norway HSR, it would have been necessary, for example, to

estimate how planned changes in the highways network would impact upon Do Minimum

demand for rail and air trips, unless it could be assumed that all such cross-modal effects would

be insignificant. By contrast, NTM5 as a multi-modal model is explicitly designed to estimate

diversion between modes.

At the outset of this study it was anticipated that a new forecasting framework would be

constructed to estimate Do Minimum demand by HSR corridor and mode, using the approach set

out above. It was anticipated that forecasting parameters (i.e. elasticities), estimated in previous

studies, would be made available for forecasting growth in air, classic rail, and road journeys.

The parameters for the different modes would then have to be made as consistent as possible,

with inclusion of cross-modal effects for changes in relative costs or journey times.

However, information on Norwegian demand parameters, even GDP (or income) elasticities and

fares elasticities, proved difficult to locate.

Avinor informed us that they do not produce separate demand forecasts for each of the domestic

air routes, and that growth of 2.1% per annum is assumed between 2011 and 2015.

NSB provided forecasts for 2009-2017 based on their transport simulation model. The latter

takes into account expected changes in journey times by mode, with allowance for capacity

limits, and reliability. Real fares are assumed to be constant. To reflect the positive effects of

increased economic activity and real disposable incomes on overall long-distance trip-rates,

NSB‟s model allows for a small positive link from GDP growth to rail demand. However, specific

income elasticities are not available.

Finally, information on forecasting future growth in Norwegian road journeys was requested from

Statens Vegvesen, who provided a full set of base (2010) and future year demand matrices from

NTM5, covering all modes.

3.2.3 Preferred Approach to Forecasting Norway HSR Do Minimum Demand

In the absence of detailed information on forecasting parameters by mode, it was decided to use

the future year matrices from NTM5. The NTM5 matrices were provided for the following years:

2010; 2014; 2018; 2024; 2043; and 2060. With an assumed opening date of 2020, the first

forecast year used in the modelling is 2018. Meanwhile, the final year, 2060, allows for demand

growth throughout a 40 year appraisal period.

Correspondence with TØI revealed that the NTM5 future year matrices are based on national

data for economic growth, and regional data for population (for the latter, see Table 3.1 above).

In addition, income elasticities are not inputs to NTM5, but can be derived from the model for

each mode, with the indirect effect of changes in car ownership exerting a significant effect.

As noted elsewhere, the NTM5 „Do Minimum‟ future year matrices allow for a number of

improvements to the road and rail networks, based mainly on the Norwegian National Transport

Plan (2010-2019). For rail, the timetable improvements are predominantly associated with

provision of double track, mostly in the intercity network around Oslo. The road and rail



enhancements assumed to be delivered in the NTM5 Do Minimum future year matrices are listed

in Appendix B.

Although the use of NTM5 future year matrices was not envisaged at the outset of work, this

approach ensures maximum compatibility of the Do Minimum growth forecasts in the HSR

assessment with the appraisal of other Norwegian transport schemes. Finally, it is worth

emphasising that the reservations about NTM5 matrices aired by NSB and Statens Vegvesen,

primarily concern the scale of long-distance car journeys in the base year (2010), rather than any

doubts about the methodology underlying future year growth.

3.3 Future Year ‘Do Minimum’ Demand Growth

This section sets out the growth assumed in the HSR Do Minimum scenario, based on future

year matrices from NTM5. Forecasts have been provided for the years 2018, 2024, 2043 and

2060, in addition to the 2010 base.

This section first presents the economic and demographic forecasts underlying the demand for

travel and then studies the forecast growth rate my mode (air, rail, car, and coach) for business

and leisure passengers. These forecasted growth trends are compared with population growth,

indicating changes to the propensity to travel as income increases.

The growth rates shown are based on city-to-city (i.e. municipality-to-municipality) travel on the

potential high speed rail corridors within Norway. As well as charts showing the growth by mode

on each corridor, Section 3.3.7 provides a comparison against the population forecasts within

NTM5. Growth rates for Sweden have been approximated using the average growth rates for

Norway taken from NTM5, in the absence of better quality data.



3.3.1 Air Growth (NTM5 2010-2060)

Figure 3.2 shows growth indices for business travel by air (2010 =100) projected forward to 2060

by NTM5. The first thing to note is that differences between the corridors are relatively small.

This is true of most of the charts in this section. In the case of air business trips, the highest

cumulative growth – between Oslo and Stavanger – exceeds that of the route with the slowest

growth – Bergen-Stavanger – by just 13 percentage points (94% and 81%, respectively).

Figure 3.2 shows a tendency for Do Minimum growth to slacken off after around 2020. This is

evident across all the corridors, but is most obvious in the case of Bergen-Stavanger. Similar

results are found in relation to all modes, and both journey purpose segments. Across all of the

domestic HSR corridors, forecast growth in business trips by air falls from 2.0% in 2011, to 1.8%

in 2018, to 1.2% in 2028. A slow decline continues thereafter, with growth reaching just 1% per

annum by the end of the appraisal period.

Figure 3.2 – Projected growth of business air travel to 2060

Figure 3.3 shows the corresponding growth forecasts for air leisure trips. The inter-corridor

differences reflect those of business travel. It should be noted, however, that leisure growth rates

are generally higher, implying a gradual reduction in the share of air travellers who are on

business from 61% in 2010 to 56% in 2060.

Figure 3.3 – Projected growth of leisure air travel to 2060

Even though the annual growth rates are relatively low, there is a potential doubling of domestic

air passengers over the next fifty years, which will need to be accommodated. Notwithstanding

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger



improvements in aircraft efficiency, the projected growth in air demand has clear implications for

carbon emissions, even if additional capacity is provided by using larger aircraft.

3.3.2 Classic Rail Growth (NTM5 2010-2060)

To reiterate, the Do Minimum growth profiles in this report are based on outputs from NTM5

provided by TØI, and are not strictly compatible with JBV Scenario A. That is, the effects of the

anticipated step-change improvement to long distance rail service frequencies are not included.

Figure 3.4 shows the growth in rail business trips between 2010 and 2060 projected on this basis

and driven almost exclusively by future expected changes in population and income.

Once again, NTM5 forecasts that the highest cumulative growth (99%) will be between Oslo and

Stavanger. As this exceeds the corresponding figure for air (94%), and as car travel has a small

(though rapidly growing) market share, this implies a modest increase in the mode share of rail

for business travel. On the other corridors, rail‟s share of business trips is forecast to decline

slightly over time.

Figure 3.4 – Projected growth of business rail travel to 2060

Figure 3.5 shows the corresponding growth indices for leisure travel by rail, which, in contrast to

air, is the dominant journey purpose for rail. Non-work related travel accounts for 79% of all trips

in 2010, rising to 83% in 2060.

Figure 3.5 – Projected growth of leisure rail travel to 2060

The forecast rise in rail leisure trips on the Oslo-Stavanger corridor reaches 176%. The lowest

cumulative growth, 131%, is forecast for the largest current rail market: Oslo-Bergen.

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand



3.3.3 Car Growth (NTM5 2010-2060)

Figure 3.6 shows NTM5‟s forecasts of growth in business travel by car between 2010 and 2060.

According to the NTM5 matrices, car travel accounts for just 13% of business trips in 2010 and

this mode share remains stable throughout the appraisal period.

The highest cumulative growth in car business trips is found on the Oslo-Kristiansand and Oslo-

Bergen corridors at 116%.

Figure 3.6 – Projected growth of business car travel to 2060

Figure 3.7 displays the corresponding growth in car leisure travel. The base 2010 mode share of

car is much higher for leisure trips at 44%. However, there are some reservations that NTM5 has

a tendency to overestimate long distance car trips. Growth in car leisure travel is forecast to be

higher than for other modes, with the growth rate on most routes over 200%, and reaching 250%

on Bergen-Stavanger.

Figure 3.7 – Projected growth of leisure car travel to 2060

In both journey purpose segments, the car growth rates are higher than those for rail on all

corridors. In the case of leisure trips especially, a significant element of this disparity will be due

to the effect of rising incomes on car ownership. However, it is worth reiterating that NTM5 does

not allow for capacity constraints on any mode, so worsening road congestion may tend to favour

rail in the years ahead.

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger

0

50,000

100,000

150,000

200,000

250,000

300,000

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger



3.3.4 Coach growth (NTM5 2010-2060)

Figure 3.8 shows the growth for coach travel forecast in NTM5 for business trips between 2010

and 2060.

The base demand for business travel by coach as forecast by NTM5 is already very low for

coach travel – under 3% market share in 2010. Journey times are long, and passengers tend to

switch to faster and more comfortable modes as rising incomes produce greater willingness to

pay to reduce travel times. Nevertheless, in the business segment there is relatively rapid growth

until around 2020, with the exception of the two shortest routes.

The cumulative growth rate to 2060 ranges between 80% Oslo-Kristiansand and 100% Oslo-

Trondheim.

Figure 3.8 – Projected growth of business coach travel to 2060

Figure 3.9 displays the corresponding growth for leisure travel by coach, which as with other

modes is higher than that for business travel, at between 120% and 160%. The lowest growth is

again on the two shortest routes. Coach has a slightly higher 2010 market share in the leisure

sector of 8%.

Figure 3.9 – Projected growth of leisure coach travel to 2060

100

120

140

160

180

200

220

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger

100

120

140

160

180

200

220

240

260

280

Oslo - Stavanger

Oslo - Bergen

Oslo - Trondheim

Oslo - Kristiansand

Bergen - Stavanger



3.3.5 Largest and Smallest Growth 2010-2060: Business Trips

This section presents the range in the growth of business trips, highlighting the modes and

corridors with the fastest and slowest growth. The charts are based on NTM5 outputs for 2010

and 2060, measured at municipality level.

Figure 3.10 confirms that for work-related travel, car tends to have the fastest expected growth

rates.

Figure 3.10 – Compound Annual Growth Rates (CAGR) – Business 2010-2060

However, when expressed in absolute terms (Figure 3.11) – that is, after allowing for the relative

sizes of the various markets in 2010 – the largest future changes in journey volumes are found in

air demand. The dominance of air over competing modes is particularly striking in this chart, and

as HSR is aimed at abstracting air demand, this finding has important implications.

Figure 3.11 – Absolute growth in annual journeys – Business 2010-2060

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%Business Growth (compound rate p.a.)

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000Business Growth (absolute 2010-2060)



3.3.6 Largest and smallest growth 2010-2060: Leisure trips

Comparing Figure 3.12 with Figure 3.10 confirms that the leisure market is expected to grow at a

faster rate than that for business trips.

Within the leisure market, future expected growth in journeys by car between Bergen and

Stavanger exhibits a significant differential over the second ranked observation, which is also for

a car flow (Oslo-Stavanger).

In fact, the top five instances of growth rates in leisure trips are all for car travel. Rail flows are

bunched in the middle of the distribution with growth at around 1.75% per annum, whilst air

growth rates show the largest variations in ranking between corridors.

Figure 3.12 – Compound Annual Growth Rates (CAGR) – Leisure 2010-2060

Figure 3.13 shows that the largest future increases in Do Minimum leisure trip volumes are again

mainly associated with car travel.

Figure 3.13 – Absolute growth in annual journeys – Leisure 2010-2060

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%Leisure Growth (compound rate p.a.)

0

50,000

100,000

150,000

200,000

250,000Leisure Growth (absolute 2010-2060)



3.3.7 Comparison with Population Growth

This section contrasts growth in demand with growth in population.

Within NTM5, the disparities in forecasts of demand growth between corridors would be expected

to reflect differences in the population projections, which are input to the model at county level

(see Table 3.1).

Population growth not only implies a direct increase in travel due to more residents, but the

fastest increases in GDP and productivity are also likely to be found where population growth is

most rapid, as skilled migrants and firms are drawn to regions with buoyant economies. This

produces a separate increase in travel demand due to higher incidence of (long distance) travel

per person (it is notable that Norway‟s high per capita income levels already produce some of the

highest long distance trip-rates found in the world).

Figure 3.14 and Figure 3.15 compare the growth indices for business and leisure travel with the

projected growth of population at the non-Oslo end of each flow. In the case of Bergen and

Stavanger, the population growth is a simple average.

Demand growth is shown for (a) the current leading mode, and (b) summed across all existing

modes. Population growth 2010-2060 is shown by the black columns.

Figure 3.14 – Comparison between population growth and growth in business travel (2010=100)

Figure 3.15 – Comparison between population growth and leisure travel (2010=100)

100

120

140

160

180

200

220

Business Growth Comparison (2010 - 2060)

Air

All modes

Pop 2010-2060

100

150

200

250

300

350

Leisure Growth Comparison (2010 - 2060)

Car

All modes

Pop 2010-2060



Figure 3.14 and Figure 3.15 show that growth in long distance travel demand is highest where

(non-Oslo) population growth is highest; that is, on the Stavanger corridor.

Across all corridors, the growth in travel outstrips the growth in population, indicating a rise in

long distance trip-rates. In the case of the business segment, demand growth across all modes

exceeds population growth by between 28 percentage points (Bergen-Stavanger) and 42

percentage points (Oslo-Trondheim). For leisure, the range is between 92 percentage points

(Oslo-Bergen) and 156 percentage points (Bergen-Stavanger). The particularly large difference

between leisure growth and business growth on the Bergen-Stavanger corridor may merit further

examination.

3.4 Comparison of Medium Term Forecasts: NTM5 versus Transport Operators

The previous section presented the growth forecasts derived from our chosen data source

NTM5b. In this section we compare medium term forecasts from NTM5 (2010-2018) against

those of the rail operator NSB and airport operator Avinor, to check for consistency and to

identify any potential weaknesses in the model data.

3.4.1 Medium Term Rail Demand Growth: NTM5 versus NSB Forecasts

NSB have provided rail demand indices for the next decade and these are summarised in Table

3.2 below.

Table 3.2 – NSB’s future rail demand indices: 2009-2017 (selected years)

2009 2011 2013 2015 2017

Oslo – Bergen 100 99 101 101 102

Oslo – Trondheim 100 102 106 106 106

Oslo – Kristiansand-Stavanger 100 96 92 92 93

The highest year-on-year growth is 2.7%, forecast for the Trondheim corridor in 2011-2012. This

will probably reflect a planned improvement to the classic rail service at that time. Meanwhile the

fall in demand on the Kristiansand-Stavanger corridor is presumably due to planned

improvements to highways. As far as the effect of rising incomes is concerned, NSB confirm a

tendency for its relatively slow long-distance services to lose market share to air travel.

Figure 3.16 below provides a comparison of medium term growth forecasts for Norwegian classic

rail from the train operator NSB and the NTM5 model.

Figure 3.16 – Medium-term rail demand growth by corridor: NSB vs. NTM5

-10%

-5%

0%

5%

10%

15%

20%

25%

30%

Oslo - Bergen Oslo - Trondheim Oslo - Kristiansand -Stavanger

NTM5 versus NSB growth to 2017/2018

NSB Growth 2009 - 2017 NTM5 Growth 2010 - 2018



It is clear that NSB‟s figures are considerably below those forecast by NTM5. The corresponding

Compound Annual Growth Rates (CAGR) are presented in Table 3.3 below.

Table 3.3 – Comparison of medium-term rail demand growth rates 2010-2018

Route NSB CAGR NTM5 CAGR

Oslo – Bergen 0.3% 2.1%

Oslo – Trondheim 0.8% 2.3%

Oslo – Kristiansand – Stavanger -0.9% 2.8%

By way of contrast, between 2003/4 and 2007/8, long-distance intercity travel in the UK grew by

around 5.6% per annum, in spite of regulated fares rising in real terms by 1% per annum37

.

However, with long-distance train speeds in Norway currently amongst the slowest in Europe, the

current („classic‟) rail service tends to lose passengers to air as incomes rise.

Leaving aside the question of whether high speed rail is a closer substitute for classic rail or air,

to be answered in the mode choice analysis, the fact that rising incomes tend to transfer

Norwegian demand from classic rail to air, suggests that tailoring the service to the requirements

of air passengers will become increasingly important.

3.4.2 Air Demand Growth: NTM5 versus Avinor Medium Term Forecasts

Table 3.4 below shows that medium-term growth in air demand in the NTM5 matrices (2010 to

2018) closely matches Avinor‟s assumption of 2.1% per annum.

Table 3.4 – Comparison of medium-term air growth rates 2010-2018

Route Avinor CAGR NTM5 CAGR

Oslo – Bergen 2.1% 1.9%

Oslo – Trondheim 2.1% 2.2%

Oslo – Kristiansand – Stavanger 2.1% 2.1%

These comparisons suggest that there is consensus on the likely growth in air passengers, but

some questions around the classic rail market. The role of HSR in Norway would be

predominantly to capture long distance trips currently served primarily by air. So for this HSR

study the consistency of air forecasts in the medium term greatly overshadows the divergence of

opinion on classic rail.

37 An element of this rapid British growth is endogenous in nature - driven by improvements in timetables and reliability.

Source: National Rail Trends 2009-2010 yearbook (Table 1.1b Passenger kilometres by sector).



3.5 Conclusions

Future year growth forecasts have been developed based upon demand matrices produced by

the NTM5 model.

The alternative – producing Do Minimum forecasts from first principles – was rejected mainly

because of the absence of detailed forecasting parameters for each mode. However, an NTM5-

based approach has a number of advantages:

NTM5 forecasts already account for committed rail and highway schemes and the impact

they will have in inducing travel demand;

Use of NTM5 ensures maximum compatibility with the growth assumptions applied in the

appraisal of other Norwegian schemes; and

In the medium term, forecast growth in air demand from NTM5 matches closely the figure of

2.1% per annum assumed for all domestic routes by Avinor, the airport operator.

The future year matrices derived from NTM5 have been analysed to understand the growth

trends by mode for each corridor. It has been shown that between the largest cities:

Business passengers today predominantly use air over long distances and, in the Do

Minimum scenario, this is reinforced over the next fifty years with the highest unconstrained

growth experienced by this mode;

On the Oslo-Bergen corridor, volumes of rail business trips are forecast to grow significantly,

although this is due to higher base demand, rather than a faster percentage growth rate;

Over the 50 year period leisure experiences higher growth than business;

Growth in Do Minimum leisure passengers is focussed on car journeys;

Measured in absolute volumes, growth in car journeys is high on all corridors for leisure travel

but negligible for business (except on the Bergen-Stavanger corridor where car is competitive

with air overall);

Growth rates on all modes are higher than the underlying population growth rate, particularly

for leisure travel indicating that greater incomes in the future will lead to increased trips;

On most corridors, the growth rate of business travel is typically higher up until around 2020

and then slowly reduces over the next 40 years;

Classic rail travel will continue to be dominated by leisure users, with an increase from 79%

to 83% of trips undertaken by leisure users. Conversely, business users‟ share of air travel

will reduce from 61% to 56%; and

In order to optimise the HSR business case, it seems appropriate to target business travellers

who currently fly, and leisure travellers who currently fly or drive. In the latter case, discounts

for group/family travel may be worthwhile.



4 HSR Demand and Revenue Forecasts 4.1 Introduction

This section of the report presents a summary of the key results for HSR demand and revenue

for each of the example HSR route options, based on the current specification of the mode

choice model. All the options – and hence demand and revenue forecasts – will be subject to

further refinement in Phase 3, taking into account outputs from the other Phase 2 contracts, the

Phase 3 alignment work, and additional data collection and analysis.

The structure of this chapter is as follows:

Brief description of the approach to the demand and revenue forecasting, including the model

assumptions, service specifications for the four scenarios, description of the representation of

Scenarios A and B in NTM5; and

Presentation of the traffic forecasts for each of the HSR corridors, for Scenarios B, C and D

where applicable.

For some routes, multiple improvement scenarios are applicable. For example, on the route

between Oslo and Bergen via Hallingdal, the improvements could range from a relatively modest

upgrade to the existing alignment (Scenario B, with small journey time savings on classic rail) to

new HSR infrastructure serving a broadly similar corridor, but with far fewer bends that limit train

speeds (Scenario D). For Scenarios C and D, it is assumed that classic rail services operate at

current service levels, supplemented by the new (limited stop) HSR services.

Section 4.2 outlines briefly the methodology applied in producing the demand and revenue

forecasts, including a list of the key assumptions. A detailed description of the approach to

demand modelling and forecasting is provided in the Model Development Report (MDR).

4.2 Approach to demand and revenue forecasting

Robust demand forecasting is fundamental in ensuring that the assessment of the options for

improving long distance rail service in Norway is credible and objective. Not only does the

demand forecasting underpin estimates of fare-box income, and hence potential subsidy

requirements, but it is also the basis of most of the economic benefits; e.g. time savings and

reductions in pollution from cars and aircraft.

As this phase of the study is required to consider the possibilities for incremental development of

long distance rail services, a dual forecasting approach has been developed.

For more modest incremental improvements to classic rail, where abstraction from air is

expected to be limited, the NTM5 model is used. This mixed methodology has been adopted

because of reservations about the use of NTM5 when modelling large step-change

improvements in rail levels of service. However, NTM5 is an established model which has been

audited by TØI, accepted as broadly fit-for-purpose, and used for the appraisal of other

Norwegian transport schemes. It is therefore retained for the relatively minor timetable

improvements under Scenarios A and B.

Section 4.2.1 describes the presentation of Scenario B outputs from NTM5.

4.2.1 Representations of Scenarios A and B

Atkins was supplied with the NTM5B network specifications and associated socio-economic data,

as used for the recent National Transport Plan work in Norway. The networks were identical for

the two forecast years under scrutiny (2024 and 2043).

In terms of target journey times and frequencies, the broad specification for these scenarios is

provided in “TN6 Scenario Testing”. In summary, Scenario A anticipates an increase in train



frequency (or reduction in service headway), whilst Scenario B anticipates an improvement in

train speed and hence reduction in journey time.

Atkins calculated the change, from the “Fastest 2010” in the Scenario Testing Note, for each

corridor, as shown in Table 4.1.

Table 4.1 – Representation of Changes in Supply in NTM5B

Corridor Scenario A: Headway Factor

Scenario B: Journey Time Factor

Oslo-Bergen 0.5 0.85

Oslo - Kristiansand -Stavanger

0.5 0.83

Oslo-Trondheim 0.33 0.85

Oslo-Stockholm 0.5 0.92

Oslo-Gothenburg 0.33 0.90

To implement these Scenarios in NTM5B, these corridor specific adjustments were applied to the

relevant services. The factors are multiplicative and were applied within the EMME data

repository.

As a result, the changes modelled in these NTM5B tests do not represent a change in stopping

pattern or variation in speed change along the corridor, merely an improvement in headway or

journey time at the strategic level. This will be adequate for end to end travel, but may not identify

more local demand responses to supply changes at a local level.

It should be noted that these changes were applied to both “day trains” and “night trains” as both

are specified in NTM5B and equally contribute to supply and are available for assignment. The

model is based on aggregate daily demand and supply levels.

In the case of Scenario A, a single NTM5B test was undertaken, with the train frequencies

improved in all five corridors.

In the case of Scenario B, a similar initial test was undertaken, with the train journey times

improved in all five corridors, mainly to give assurance that the model would respond

appropriately to a more marked improvement in the supply side. This was followed by testing one

corridor at a time, as proposed in the Scenario Testing Note; the latter results are those reported

here.

Section 4.2.2 describes the presentation of Scenario C and D outputs from the bespoke demand

forecasting model.

4.2.2 Representations of Scenarios C and D

For the major interventions envisaged under Scenarios C and D – which involve new

infrastructure and potentially high specification rolling stock – a specially-developed mode choice

model is applied. The latter has parameters (essentially „values of time‟ by mode) estimated in an

associated „Stated Preference‟ (SP) exercise using survey responses from a large panel of

Norwegian volunteers38

.

Assumptions

The most important modelling assumptions employed in the bespoke demand model are listed as

follows:

38 For more information, see the Final Report for Subjects 2 and 3 (Market Analysis).



Zoning: In the main cities, excluding Kristiansand, the model zones are urban districts

(bydeler). Elsewhere they are municipalities (kommuner), or in sparsely-populated areas,

groups of municipalities with joint population of approximately 60,000. With Stockholm,

Gothenburg and Gardermoen airport added as „point zones‟, there is a total of 107 zones.

Mode choice structure: The mode choice model is based on the results of SP/ willingness

to pay surveys. The model considers the mode choice between air and high speed rail at an

absolute level and at increments around the demand from other modes, based on a reduced

composite cost of fast modes following the introduction of high speed rail.

Mode choice parameters: The results presented in this report use the models and

parameters estimated from SP survey analysis. A full description of the surveys and

estimated models is included in the „Subjects 2 and 3: Expected Revenue and Passenger

Choices Final Report‟.

Access and Egress times:

- HSR and Air: For each zone, the average access/egress time applicable for (a) each

major airport and (b) each potential HSR station site is estimated using GIS, allowing for

the quality of the highway network („link speeds‟ range between 20kph and 90kph), and

the distribution of population within the zone; and

- Access/egress time penalty weightings: Access/egress time weighting, relative to in-

vehicle time, is provided by the SP surveys. Where access times exceed 120 minutes,

the maximum access time considered in the SP surveys, an additional access time

weighting of 1.5 is applied.

HSR in-vehicle times and service frequencies: are based on the levels of service for

Scenarios C and D, as presented by JBV in October 2010 (see Table 4.2).

Air, coach and classic rail levels of service: are assumed to be the same as the Do

Minimum in Scenarios C and D.

Air and HSR service frequency penalties: The impact of improvements in air or HSR

service frequency is included in the estimated model and considers a set penalty divided by

the number of services in a day, this effectively considers service frequency as a headway.

Air and HSR fares: Average domestic air fares for leisure and business travel between the

principal Norwegian airports are based on Avinor‟s survey of air passengers (2009). As a

default, it is assumed that HSR fares are set equal to air fares. However, for scenario D an

additional sensitivity test is shown to demonstrate the demand impacts of lower HSR fares,

assumed to be around 60% of existing HSR fares – broadly comparable to current existing

rail fare levels39

.

Air in-vehicle times: are based on a combination of internet research, plus use of NTM5

data for flows to/from minor airports.

Wait Times: wait times for air and high speed rail have been taken as those stated by

existing users in the stated preference surveys, classic rail wait times have been used to

approximate the waiting times for a high speed rail service. The time waiting at airports

before take-off has been calculated at approximately 40 minutes in excess of that spent at an

HSR station before departure.

Generation: A logsum formulation is used to calculate the change in overall accessibility

between zones as a result of introducing high speed rail. The increased levels of trip making

as a result are calculated using an exponential formulation to forecast the increase in trips as

a result of the improved levels of accessibility.

39 For sake of clarity, only Scenario D test results are reported for the two fare levels, to demonstrate fare

sensitivity. Scenario C results are only reported for HSR fares set to existing fare levels.



HSR intermediate stops: For Scenarios A and B, as there are relatively minor

improvements to line speeds and capacity, it is assumed that rail services continue to follow

the same stopping pattern, as coded in the NTM5 model. For Scenario C it is assumed that

services call at all potential HSR stations (within the most significant towns). For example, on

the route between Oslo and Stavanger, intermediate stops are assumed at Drammen,

Porsgrunn, Arendal, and Kristiansand. For Scenario D, an intermediate stop is assumed to

add 10 minutes to the end-to-end journey time, and fewer stops are assumed.

HSR revenue: HSR fares are based on average air fares at 2009 prices.

Other modes’ monetary costs and journey times: The structure of the mode choice model

does not require these „Generalised Cost‟ data for other modes as abstraction from car,

classic rail and coach is based on incremental changes from existing journey volumes.

‘Nesting’ parameters: which reduce the sensitivity of modal shift between HSR and „slow

modes‟ (car, classic rail and bus), relative to that between HSR and air are included in the SP

model estimation.

Further detail of the assumptions applied in modal choice, and future year growth, are provided in

the supplementary Model Development Report. We emphasise the assumption that existing air

and rail services are assumed to be retained after introduction of HSR services – this assumption

may be refined in Phase 3 of the overall project.

4.2.3 Rail service specification by Corridor and Scenario

In producing the forecasts presented in this report, the rail levels of service (i.e. end-to-end

journey times, and service headways) have been set to reflect the journey times and frequencies

shown in Table 4.2. For Scenarios C and D, modelled within the bespoke HSR model, these

levels of service are applied to HSR, whilst for Scenarios A and B the improvements are made to

classic rail timetables, as represented in the NTM5 model. The in-vehicle times between stations

for Scenarios C and D in the demand forecasting model have been calculated using the rail

distances between the station stops.

Table 4.2 – HSR / Classic Corridor Level of Service by Scenario

Fastest 2010

Classic Rail

Scenario A,

Classic Rail

Scenario B

Classic Rail

Scenario C

High Speed Rail

Scenario D

High Speed Rail

Time Freq Time Freq Time Freq Time Freq Time Freq

Oslo-Kristiansand

04:25 240 04:20 120 03:30 120 03:00 60 02:10 60

Oslo-Stavanger

07:42 240 07:30 120 06:15 120 05:30 60 02:30 60

Oslo-Bergen 06:28 240 06:30 120 05:30 120 04:30 60 02:30 60

Oslo-Trondheim

06:38 360 06:30 120 05:30 120 04:30 60 02:45 60

Oslo-Stockholm

06:07 240 06:00 120 05:30 120 04:00 60 03:00 60

Oslo-Gothenburg

03:55 360 03:30 120 03:10 120 03:00 60 02:30 60

Bergen-Stavanger

- - - - - - - - 01:35 120



4.3 Traffic forecasts on national corridors

Initial results for each of the domestic HSR corridors are presented in the remaining subsections

of this chapter. Where multiple route options are available on a given corridor, a separate set of

results is provided for each. In addition a range of results is shown for Scenario D, based on the

testing of fare sensitivities and the provision of a connection to Gardermoen Airport via a

connecting service from Oslo Central.

Each set of results in Sections 4.4 – 4.11 for Scenarios A and B includes:

Corridor train passenger flows;

Demand by mode and purpose for the corridor and mode share; and

Spatial pattern of rail demand by journey purpose and growth in demand from Scenario A (Do

Minimum) to Scenario B.

The corresponding set of results for Scenarios C and D includes:

Total HSR revenue and journeys, with separation of work-related (business) and non-work

(or leisure) demand;

HSR yields (average fares) for business and leisure;

Origin-destination HSR journeys by type of flow. That is, journeys are divided as follows:

- End-to-end journeys, e.g. Oslo/Akershus – Bergen;

- Journeys between intermediate stations and an endpoint, e.g. Oslo/Akershus – Gol; Gol

to Bergen;

- Journeys between an endpoint and a zone on another HSR corridor, e.g. Bergen –

Kristiansand; and

- Residual („Other‟) journeys.

Percentage mode share on interurban flows (end-to-end journeys) for the corridor;

Highest abstraction of journeys based of county, mode of transport and journey purpose

(business or leisure); and

GIS output showing the spatial pattern of originating journeys (i.e. HSR boardings) by zone,

plus daily boardings by HSR station, assuming equal demand on each day of the week.

In addition, Appendix C presents detailed annual demand tables showing (a) HSR abstraction by mode and

generation, by type of flow, and (b) county-county HSR matrices. The routes to be tested are summarised in

Table 4.3 below. Not all combinations of test results are included in this report.

Table 4.3 – Summary of HSR Routes and Scenarios tested

Route Example HSR Stops Test Scenarios

Oslo – Bergen Hønefoss, Gol, Geilo, Voss A – D

Oslo – Bergen/Stavanger (Haukeli) Drammen, Kongsberg, Bø, Odda D only

Bergen – Stavanger Haugesund, Leirvik (Stord) D only

Oslo – Kristiansand – Stavanger Drammen, Porsgrunn, Arendal, Kristiansand A – D

Oslo – Trondheim Gardermoen, Hamar, Lillehammer, Otta A – D

Oslo – Stockholm Lillestrøm, Kongsvinger, Karlstad A – D

Oslo – Gothenburg Ski, Moss, Sarpsborg/Fredrikstad, Halden A – D



4.4 Oslo – Bergen corridor

This broad corridor can be provided / upgraded according to Scenario B (upgrade) Scenario C

(major upgrade, with some new route sections) or Scenario D (High Speed Rail with completely

new infrastructure).

4.4.1 Scenario B

Applying Scenario B on this corridor would entail improvements (e.g. partial double-tracking) of

the existing route to Bergen via Drammen, Hønefoss and Gol to allow for reductions in journey

time.

Corridor Train Passenger Flows

The following graphs show the pattern of train passengers on the main service modelled in this

corridor (the day train from Oslo to Bergen and back to Oslo, referred to as service “041a” in

NTM5B), for the following four key tests:

Scenario A for 2024 (Figure 4.1); and

Scenario B for 2024 (Figure 4.2).

These flows are in terms of passengers per day; over the modelled period of 12 hours the train is

assumed to operate every 2 hours. Please note that the scale differs from one figure to another.

It can be seen that, in the section nearest to Oslo, the train is relatively lightly loaded, with a

substantial increase in passengers boarding at Drammen and a markedly higher level of demand

between there and Bergen. The same pattern is apparent in the reverse direction of travel.

It can be seen that the peak level of passengers carried in Scenario A in 2024 is of the order of

1,700 per day, rising to around 1,900 with the improved journey time offered in Scenario B.

Figure 4.1 – Scen A (2024) Bergen Daily Demand Profile



Figure 4.2 – Scen B (2024) Bergen Daily Demand Profile

Pattern of Demand by Mode and Purpose

The pattern of total demand within the Oslo – Bergen corridor is summarised in Table 4.4 for both

the modelled years. The rail element of this demand is further analysed in the following section.

It is observed that the modal shift exhibited by NTM5B in response to this improved rail journey

time, even at the corridor level, is relatively modest. The change in modal shift from 2024 to 2043

is even more modest, but this is to be anticipated as the NTM5B model does not take account of

any road congestion or crowding on trains. It is assumed that the small increase in the air share

is driven by assumptions on costs and values of time, as the Level of Service (LoS) inputs are

held constant over time.

Table 4.4 – Corridor Demand by Mode and Purpose (Scenarios A and B1)

Scenario A: 2024 Scenario A: 2043

Demand Total Work Propn. Total Work Propn.

Car 13375 1399 10% 17888 1660 9%

Bus 1226 146 12% 1572 171 11%

Boat 237 30 13% 277 33 12%

Train 2748 613 22% 3575 733 21%

Air 3365 2266 67% 4295 2778 65%

Total 20950 4454 21% 27608 5375 19%

Mode Share

Car 64% 31%

65% 31%

Bus 6% 3%

6% 3%

Boat 1% 1%

1% 1%

Train 13% 14%

13% 14%

Air 16% 51%

16% 52%

Total 100% 100%

100% 100%



Scenario B1: 2024 Scenario B1: 2043


Car 13332 1394 10% 17832 1654 9%

Bus 1219 146 12% 1564 170 11%

Boat 235 30 13% 275 33 12%

Train 3063 706 23% 3985 845 21%

Air 3347 2258 67% 4273 2769 65%

Total 21196 4533 21% 27929 5471 20%

Mode Share

Car 64% 31%

65% 31%

Bus 6% 3%

6% 3%

Boat 1% 1%

1% 1%

Train 15% 16%

14% 16%

Air 16% 51%

15% 52%

Total 100% 100%

100% 100%

Spatial Pattern of Rail Demand

The following table (Table 4.5) shows more detailed results for rail passenger demand in the

Oslo – Bergen corridor, providing a breakdown between end-to-end trips and journeys to/from

intermediate areas.

Under the Do Minimum (Scenario A), there is a forecast increase in rail demand within the

corridor of 30% between the two modelled years, although the figure is lower for work related

trips. For both work-related trips and total trips, the end to end patronage (Oslo to Bergen or vice

versa) is significant, at nearly 50% of all rail trips, and with the fastest growth.

Table 4.5 – Rail demand by trip type and exogenous growth (Scenario A 2024 to 2043)

Scenario A: 2024 Scenario A: 2043 Growth over 2024

From To Total Work Total Work Total Work

Oslo Bergen 562 146 746 178 33% 22%

Bergen Oslo 562 146 746 178 33% 22%

Oslo Corridor 564 96 731 113 30% 18%

Corridor Oslo 564 96 731 113 30% 18%

Bergen Corridor 149 47 185 54 24% 16%

Corridor Bergen 149 47 185 54 24% 16%

Corridor Corridor 190 35 240 41 26% 17%

Total in Corridor 2741 612 3566 732 30% 20%

Oslo-Bergen as share

41% 48% 42% 49%

As shown in Table 4.6, the additional rail demand induced by the improved journey time offered

in Scenario B is around 12%, with the greatest impact found in end-to-end work-related journeys

(19%).



Table 4.6 – Impact of Scenario B1 (additional rail journeys over Do Minimum 2024, 2043)

Scenario B1: 2024 Scenario B1: 2043

From To Total Work Total Work

Oslo Bergen 16% 19% 15% 19%

Bergen Oslo 16% 19% 15% 19%

Oslo Corridor 9% 12% 9% 12%

Corridor Oslo 9% 12% 9% 12%

Bergen Corridor 9% 11% 9% 12%

Corridor Bergen 9% 11% 9% 12%

Corridor Corridor 7% 8% 7% 8%

Total in Corridor 12% 15% 11% 15%

4.4.2 Scenario C (Stopping at Hønefoss, Gol and Voss)

Applying Scenario C on this corridor would entail more significant infrastructure investment than

Scenario B, in order to deliver faster and more frequent rail services. Some new route sections

are likely, „short cutting‟ circuitous sections of the existing route, and resulting in larger end-to-

end journey time savings. An example would be the building of a new direct line from Oslo to

Hønefoss, to replace the current route via Drammen.

Table 4.7 below presents a summary of the overall demand results for an example Scenario C

option between Bergen and Oslo via Hallingdal, assuming intermediate stops at Hønefoss, Gol

and Voss.

Table 4.7 – Summary of HSR Demand and Revenue: Scenario C Oslo – Bergen (Hallingdal route via

Hønefoss, Gol and Voss) 2024

Demand Annual [k] Per day [k]

Total HSR journeys 1100 3.1

HSR Business journeys 700 1.8

HSR Leisure journeys 500 1.2

HSR Passenger kilometres (million) 400 1.0

Revenue and yield Annual [NOK million] Average yield [NOK]

HSR Total revenue 700 600

HSR revenue from Business travel 500 700

HSR revenue from Leisure travel 200 500

It can be seen that annual journeys in 2024 are estimated at 1.1 million, averaging around 3100

per day. This demand breaks down as 59% business journeys, and 41% leisure journeys. Total

annual revenue is estimated at approximately 700 NOK million, with an average (one way) yield

of 700 NOK per journey for business, and 500 NOK for leisure.

Table 4.8 below provides a breakdown of annual journeys by type of flow, and Table 4.9 shows

estimated daily boardings by station.



Table 4.8 – HSR Demand by Origin/Destination type: Scenario C Oslo – Bergen (Hallingdal route via


Oslo-Bergen Annual Total (k) Business (k) Leisure (k)

Oslo/Akershus - Bergen 400 250 150

Oslo/Akershus - Intermediate area 250 150 150

Bergen - Intermediate area 50 50 50

Oslo/Akershus - Other HSR corridors 100 50 50

Bergen - Other HSR corridors 100 50 50

Other 200 100 50

Total 1100 650 450

Table 4.8 shows that end-to-end journeys account for over a third (37%) of all trips, ranging

between 36% of leisure trips and 37% of business trips.

A further 30% of trips are between Greater Oslo and intermediate areas, with 17% between

Greater Oslo and other HSR corridors. Some within the category are journeys to/from zones in

the Trondheim corridor, with access to HSR via the intermediate stations at Hønefoss and Gol. If

the Trondheim corridor were provided as well as the Bergen corridor, these trips would fall away

significantly.

Table 4.9 – Boardings by station Scenario C Oslo – Bergen (Hallingdal route via Hønefoss, Gol and

Voss) 2024

Station Daily boardings (k) % of total Cumulative for route

Oslo 1.3 41% 1.3

Hønefoss 0.1 3% 1.4

Gol 0.1 3% 1.5

Voss 0.4 14% 1.9

Bergen 1.2 39% 3.1

Table 4.9 shows that boardings at two of the intermediate stations – Hønefoss and Gol –

represent only a small fraction of the overall market which produces a total of around 3,000

boardings per day. Voss represents a more significant proportion of daily boardings, less than

half that of Oslo or Bergen.

Figure 4.3 below shows the forecast mode shares for end-to-end trips in 2024 under Scenario C.

Air travel accounts for almost a third of the overall market, followed by car and classic rail. HSR

accounts for under a fifth of the market for trips between Oslo and Bergen.



Figure 4.3 – Mode Share: Scenario C Oslo – Bergen via Hønefoss, Gol and Voss 2024

(Oslo/Akershus-Bergen)

Figure 4.4 below shows the major sources of demand abstracted by HSR. These journey data

are disaggregated by previous mode, journey purpose and originating county. With Bergen

located within Hordaland county, it is clear from the chart that end-to-end air trips are the

principal source of abstracted demand.

Figure 4.4 – Highest abstraction of journeys: Scenario C Oslo – Bergen (Hallingdal route via


26%

22%30%

4%

18%

HSR

Car

Air

Bus

Classic Rail

0

20000

40000

60000

80000

100000

120000

140000

160000

Abstracted originating jnys



Figure 4.5 provides a GIS presentation of the spatial pattern of annual HSR trip-ends and daily

HSR station boardings. HSR trip-ends are concentrated in the bydeler (i.e. urban districts) within

the two cities, with 75% of boardings at either Bergen or Oslo. In addition, a significant share of

the boardings at Voss is by passengers accessing from areas to the east of Bergen. The

relatively weak demand for HSR boardings (and alightings) at Gol and Hønefoss – as shown in

Table 4.9 – is confirmed by the map.

Figure 4.5 – HSR demand by originating zone (annual) and point of boarding (daily)



4.4.3 Scenario D (with stop at Voss)

Applying Scenario D on this corridor would involve the construction of completely new HSR

infrastructure, following a broadly similar corridor to the existing line but with far fewer bends that

limit train speeds. This will allow for a very significant reduction in journey time and an increase in

the frequency of rail services.

Table 4.10 below presents a summary of the overall demand results for an example Scenario D

option between Bergen and Oslo, assuming an intermediate stop at Voss. The range of demand

shown is based on the various sensitivities tested. The lowest demand shown is based on HSR

fares equalling current air fares. The highest demand is based on the sensitivity where HSR fares

are assumed to equal current rail fares (60% of air fares) and there is provision for a connecting

service from Oslo Central to Gardermoen Airport. In terms of revenue, the lowest revenue shown

is based on HSR fares equalling rail fares and there is no connection to Gardermoen, while the

highest revenue corresponds to the option with HSR fares equalling air fares and a connecting

service from Oslo Central to Gardermoen Airport.

Table 4.10 – Summary of HSR Demand and Revenue: Scenario D Oslo – Bergen (via Voss) 2024


Total HSR journeys 1500 – 2500 4.2 – 6.8

HSR Business journeys 1000 – 1400 2.6 – 4.0

HSR Leisure journeys 600 – 1000 1.6 – 2.8

HSR Passenger kilometres (million) 600 – 1000 1.6 – 2.7


HSR Total revenue 700 – 1300 400 - 700

HSR revenue from Business travel 500 – 900 500 - 800

HSR revenue from Leisure travel 300 - 400 300 - 500

It can be seen that annual journeys in 2024 are estimated at between 1.5 and 2.5 million,

averaging around 4,200 to 6,800 per day. This demand breaks down as 62% business journeys,

and 38% leisure journeys. Total annual revenue is estimated at between 0.7 and 1.3 NOK billion,

with an average (one way) yield of 500 to 800 NOK per journey for business, and 300 to 500

NOK for leisure. Total rail passengers (including both HSR and on the existing rail services) on

the corridor are forecast to be around 2.1m to 3m trips per year in 2024.

Table 4.11 below provides a breakdown of annual journeys by type of flow, and Table 4.12

shows estimated daily boardings by station.

Table 4.11 – HSR Demand by Origin/Destination type: Scenario D Oslo – Bergen (via Voss) 2024

Oslo-Bergen via Voss Annual Total (k) Business (k) Leisure (k)

Oslo/Akershus - Bergen 600 – 800 400 – 500 200 – 300

Oslo/Akershus - Intermediate area 400 – 500 200 200 – 250

Bergen - Intermediate area 75 – 100 50 – 75 0 – 50

Oslo/Akershus - Other HSR corridors 150 – 200 75 – 100 50– 100

Bergen - Other HSR corridors 100 – 500 100 – 300 50 – 200

Other 200 – 500 150 – 300 50 – 200

Total 1550 – 2500 950 – 1400 600 – 1000



Table 4.11 shows that end-to-end journeys account for over a third (40%) of all trips, ranging

between 39% of leisure trips and 42% of business trips. A further 30% of trips are between

Greater Oslo and intermediate areas, with 17% between Greater Oslo and other HSR corridors.

Table 4.12 – Boardings by station: Scenario D Oslo – Bergen (via Voss) 2024


Oslo S 1.9 – 2.4 41 - 46% 1.9 – 2.4

Voss 0.6 – 0.8 13 - 14% 2.5 – 3.2

Bergen 1.7 – 2.7 40 - 46% 4.2 – 5.9

Table 4.12 shows that boardings at the intermediate station (Voss) represent a sizable proportion

of the overall market which produces a total of between 4,200 and 5,900 HSR boardings per day.

The daily boardings at Voss are approximately a third the amount of boardings at Bergen.

Figure 4.6 below shows the forecast mode shares for end-to-end trips in 2024 under this

Scenario. HSR accounts for almost 40% of the market, which is slightly lower than for the non-

stop service. Disaggregation by journey purpose would show that air commands a larger share of

business trips, and car a larger share of leisure trips.

Figure 4.6 – Mode Share: Scenario D Oslo – Bergen via Voss 2024 (Oslo/Akershus-Bergen)

38%

19%

23%

3%

16%

HSR

Car

Air

Bus

Classic Rail




are disaggregated by previous mode, journey purpose, and originating county. With Bergen

located within Hordaland county, it is clear that end-to-end air trips are, once again, the principal

source of demand abstracted by HSR.

Figure 4.7 – Highest abstraction of journeys: Scenario D Oslo – Bergen (via Voss) 2024

Figure 4.8 provides a GIS presentation of the spatial pattern of annual HSR trip-ends, and daily

HSR station boardings. It can be seen that HSR trip-ends are concentrated in the bydeler (i.e.

urban districts) within the cities of Bergen and Oslo. There is also a significant number of

boardings shown at Voss. This demand is drawn largely from areas to the north and west of the

town.

0

50000

100000

150000

200000

250000





4.4.4 Bergen Corridor Summary and Conclusions

The existing route via Drammen, Hønefoss, Geilo and Gol, known as the Hallingdal route, can be

upgraded using Scenarios B, C or D. A key infrastructure enhancement for Scenarios C and D

would be to construct a new direct line between Oslo and Hønefoss, significantly reducing

journey times.

For Scenario D, the example case presented is for only one intermediate station at Voss, serving

area to the north of Bergen. In this instance, the total rail market could be between 2.1m and

3.0m trips per year (4,200 – 6,800 daily) in 2024, with HSR revenue estimated at between 0.7

and 1.3bn NOK per year. Of the demand, 33% is generated, with 40% abstracted from air and

17% from car.



4.5 Bergen/Stavanger – Oslo corridor (Haukeli route – Y shaped route)

The route via Haukeli can only be provided with new HSR infrastructure (Scenario D), including a

new line between Drammen and Bergen via Bø and Odda. This route allows for a branch to

Stavanger, providing additional revenue and benefits.

This Y-shaped example option could either be operated with separate Oslo-Bergen and Oslo-

Stavanger services, or alternatively trains from Oslo could divide at an intermediate station. The

results below assume the former.

4.5.1 Scenario D (non-stop)


infrastructure, following a broadly similar corridor to the existing line, with far fewer bends that

limit train speeds. This will allow for a very significant reduction in journey time, and an increase

in the frequency of rail services.


option between Bergen/Stavanger and Oslo via Haukeli, assuming that there are no intermediate

stops. The range of demand shown is based on the various sensitivities tested. The lowest

demand shown is based on HSR fares equalling current air fares. The highest demand is based

on the sensitivity where HSR fares are assumed to equal current rail fares (60% of air fares) and

there is provision for a connecting service from Oslo Central to Gardermoen Airport. In terms of

revenue, the lowest revenue shown is based on HSR fares equalling rail fares and there is no

connection to Gardermoen, while the highest revenue corresponds to the option with HSR fares

equalling air fares and a connecting service from Oslo Central to Gardermoen Airport.

Table 4.13 – Summary of HSR Demand and Revenue: Scenario D Oslo – Bergen/Stavanger (Haukeli

route non-stop) 2024







HSR Total revenue 1500 - 2500 500 - 800

HSR revenue from Business travel 1100 - 1800 500 - 900



averaging between 6,800 and 11,300 per day. This demand breaks down as 63% business

journeys, and 37% leisure journeys. Total annual revenue is estimated at between 1.5 and 2.5

NOK billion, with an average (one way) yield of 500 to 900 NOK per journey for business, and

400 to 600 NOK for leisure. Total rail trips on the corridor (including both existing rail corridors

and the new HSR service) are expected to be around 4.4m to 6.0m per year in 2024.

Table 4.14 below provides a breakdown of annual journeys by type of flow for the Oslo-Bergen

and Oslo-Stavanger corridors, and Table 4.15 shows estimated daily boardings by station for the

Bergen and Stavanger services.



Table 4.14 – HSR Demand by Origin/Destination type: Scenario D Oslo – Bergen/Stavanger (Haukeli

route non-stop) 2024

Oslo-Bergen/Stavanger Annual Total (k) Business (k) Leisure (k)

Oslo/Akershus – Bergen 700 – 850 450 – 500 250 – 350

Oslo/Akershus – Stavanger 450 – 600 300 – 350 150 – 200

Oslo/Akershus – intermediate Bergen corridor

300 – 350 150 – 175 100 – 150

Oslo/Akershus – intermediate Stavanger corridor

350 – 450 200 – 250 150 – 200

Bergen – Intermediate area 50 – 100 50 – 75 0 –50

Stavanger – Intermediate area 75 – 100 50 – 75 0 – 550

Bergen – Other HSR corridors 550 - 1000 350 – 650 400 – 200

Stavanger – Other HSR corridors 350 – 1150 200 – 700 150 – 450

Total Demand 4150 – 2500 2450 – 1600 1700 – 900

Table 4.14 shows that end-to-end journeys account for almost half (46%) of all trips, ranging

between 44% of leisure trips and 47% of business trips. Of these end-to-end journeys, 59% were

made between Oslo and Bergen, and 41% between Oslo and Stavanger. A further 25% of trips

are between Greater Oslo and intermediate areas, with 43% in the Bergen corridor and 57% in

the Stavanger corridor. It should be noted that with no intermediate stations assumed, these

journeys require passengers to „double-back‟ after arrival at Bergen, Stavanger or Oslo.

Table 4.15 – Boardings by station: Scenario D Oslo – Bergen/Stavanger (Haukeli route non-stop) 2024


Oslo 3.3 – 4.0 41 - 49% 3.3 – 4.0

Bergen 1.8 – 3.0 27 - 30% 5.1 – 7.0

Stavanger 1.7 – 2.8 25 - 29% 6.8 – 9.8

Table 4.15 shows there are slightly more boardings at Bergen than there are at Stavanger. The

approximate HSR boardings per day on Bergen services between 1,800 and 3,000, compared to

1,700 to 2,800 for Stavanger services.

Figure 4.9 below shows the forecast mode shares for end-to-end trips in 2024 between Oslo and

Bergen under Scenario D. HSR achieves a market share of just over 40%, with air, car and the

slow public transport modes (i.e. classic rail plus bus) each accounting for approximately a fifth of

the market. Disaggregation by journey purpose would show that air commands a larger share of

business trips, and car a larger share of leisure trips.



Figure 4.9 – Mode Share: Scenario D Oslo – Bergen non-stop 2024 (Oslo/Akershus-Bergen)

Figure 4.10 below shows the corresponding mode shares for end-to-end trips between Oslo and

Stavanger in 2024 under Scenario D. HSR has a share of nearly half of the overall market, with

air having a quarter share. As with Oslo – Bergen, car captures nearly 20% of the market and

disaggregation by journey purpose would show that air commands a larger share of business

trips, and car a larger share of leisure trips. Classic rail has a smaller market share than between

Oslo and Bergen.

Figure 4.10 – Mode Share: Scenario D Oslo – Stavanger non-stop 2024 (Oslo/Akershus-Stavanger)


are disaggregated by previous mode, journey purpose, and originating county. With Bergen

located within Hordaland county and Stavanger in Rogaland, it is clear from the chart that end-to-

end business air trips are the principal source of abstracted demand.

41%

19%

22%

3%

15%

HSR

Car

Air

Bus

Classic Rail

46%

19%

25%

3%7%

HSR

Car

Air

Bus

Classic Rail



Figure 4.11 – Highest abstraction of journeys: Scenario D Oslo – Bergen/Stavanger (Haukeli route

non-stop) 2024


HSR station boardings. It can be seen that HSR trip-ends are concentrated in the bydeler (i.e.

urban districts) within the cities of Bergen, Stavanger and Oslo, with significant demand to the

north of Bergen and immediately south of Stavanger.

0

50000

100000

150000

200000

250000

300000





4.5.2 Bergen Corridor (Haukeli Route) Summary and Conclusions

The Haukeli route follows a completely new alignment between Bø and Bergen and can be

constructed in conjunction with a branch to Stavanger. Analysis of this route with a combination

of Oslo – Bergen and Oslo – Stavanger services suggests that it will induce far higher demand

and produce more revenue, albeit probably at a greater construction cost, than a single route to

Bergen.

For the Haukeli route tested, the total HSR market could be around 1.5 to 2.5m trips per year

(6,800 – 11,300 daily) in 2024, with revenue of between 1.5 and 2.5bn NOK per year. Total rail

trips on the corridor (both HSR and existing rail services) are forecast to be around 4.4m to 6m

per year in 2024. The sources of demand are similar to the other routes to Bergen with 33%

demand generated, 16% abstracted from car and 42% abstracted from air. In reality it is likely

that the strongest case for this route would include a stop at Drammen to serve the west of Oslo

and provide connectivity with other routes. The impact of the stop at Drammen is currently

underestimated in the model as it excludes base trips of 100km or less.

Further work will be required in Phase 3 to determine the exact level of service on this route;

whether to alternate trains between Bergen and Stavanger or to split trains en-route. There will

need to be investigation into the potential of a HSR stop at Haugesund on the branch to

Stavanger. Refinement to the model will be required to estimate passenger movements around

the suburbs of Oslo and interaction with the improved regional services enabled by the InterCity

Study.



4.6 Stavanger – Bergen corridor (Haugesund route)

The route via Haugesund can only be provided with new HSR infrastructure (Scenario D), as it

would be an entirely new construction, serving a corridor where there is currently no rail

infrastructure.

This corridor would likely be constructed in parallel with another corridor – either Oslo – Bergen,

Oslo – Stavanger or Oslo – Bergen and Stavanger. However, for the purpose of this report the

corridor has been tested in isolation.

4.6.1 Scenario D (with stop at Haugesund)






option between Stavanger and Bergen, assuming a stop at Haugesund. The range of demand



are assumed to equal current rail fares (60% of air fares). In terms of revenue, the lowest

revenue shown is based on HSR fares equalling rail fares, while the highest revenue

corresponds to the option with HSR fares equalling air fares.

Table 4.16 – Summary of HSR Demand and Revenue: Scenario D Stavanger – Bergen (via

Haugesund) 2024






Revenue and yield Annual [NOK, millions] Average yield [NOK]







NOK billion, with an average (one way) yield of 500 to 800 NOK per journey for business, and

200 to 400 NOK for leisure.





Table 4.17 – HSR Demand by Origin/Destination type: Scenario D Stavanger – Bergen (via

Haugesund) 2024

Stavanger-Bergen via Haugesund

Annual Total (k) Business (k) Leisure (k)

Stavanger-Bergen 250 – 300 175 – 200 50 – 75

Stavanger-Corridor 1 1 0

Bergen-Corridor 100 – 150 100 – 125 25 – 50

Stavanger-Other corridors 75 – 100 50 – 75 25 – 50

Bergen-Other corridors 200 – 250 100 – 150 50 – 75

Other 100 – 150 75 – 100 25 – 50

Total 750 – 900 550 – 650 200 – 250

Table 4.17 shows that end-to-end journeys account for nearly a third (31%) of all trips, ranging

between 33% of business trips and 27% of leisure trips. A further 19% of trips are between

Bergen and intermediate areas and almost no travel between Stavanger and intermediate areas.

24% of demand is between Bergen and other HSR corridors and 11% is between Stavanger and

other HSR corridors.

Table 4.18 – Boardings by station: Scenario D Stavanger – Bergen (via Haugesund) 2024


Stavanger 0.8 – 1.0 38% 0.8 – 1.0

Haugesund 0.3 12 - 13% 1.0 – 1.3

Bergen 1.0 – 1.2 49% 2.0 – 2.5

Table 4.18 shows that boardings at the intermediate station (Haugesund) represent a sizable

proportion of the overall market which produces a total of between 2,000 and 2,500 HSR

boardings per day.

Figure 4.13 below shows the forecast mode shares for end-to-end trips in 2024 under Scenario

D. HSR accounts for 34% of the market, with air only 13%. Car travel still dominates in this

corridor with nearly half the market share while bus has a 6% share. There are is negligible

demand for classic rail as there is no such service in this corridor. Disaggregation by journey

purpose would show that air commands a larger share of business trips and car a larger share of

leisure trips.



Figure 4.13 – Mode Share: Scenario D Stavanger – Bergen via Haugesund 2024 (Stavanger-Bergen)


are disaggregated by previous mode, journey purpose, and originating county. With Stavanger

located within Rogaland county, it is clear from the chart that end-to-end business air and car

trips are the principal source of abstracted demand.

Figure 4.14 – Highest abstraction of journeys: Scenario D Stavanger – Bergen (via Haugesund) 2024


HSR station boardings. The majority of the demand is centred around the cities of Stavanger and

Bergen, and also the intermediate station at Haugesund.

34%

46%

13%

6% 1%

HSR

Car

Air

Bus

Classic Rail

0

2000

4000

6000

8000

10000

12000

14000

16000

18000





4.6.2 Stavanger – Bergen Corridor Summary and Conclusions

The Stavanger – Bergen route can only be implemented under Scenario D as it will involve the

construction of a new rail line for the entirety of the route, as there is no existing direct rail link

between the two cities. The example option shown in this report has an intermediate stop at

Haugesund. The total HSR market for this route is currently estimated at around 0.7 to 0.9m trips

per year (2,000 – 2,500 per day) in 2024, with revenue of between 0.4 and 0.6bn NOK per year.

Of this demand, 40% is generated, with 24% abstracted from car and 34% from air.

As the Stavanger – Bergen route is a completely new construction, traversing several fjords and

mountainous areas, the construction costs for the route could possibly be prohibitive, especially

when considering the lack of a direct connection to Oslo. In Phase 3, there will be scope to

examine the construction of the Stavanger – Bergen route in combination with the

implementation of HSR on either the Oslo – Bergen, Oslo – Stavanger or Oslo –

Bergen/Stavanger corridors. This will attract increased demand and generate higher revenue.



4.7 Stavanger – Kristiansand – Oslo corridor

This broad corridor can be provided/upgraded according to Scenario B (upgrade) Scenario C

(major upgrade, with some new route sections alignments) or Scenario D (High Speed Rail with

completely new infrastructure).

4.7.1 Scenario B


the existing route to Stavanger via Drammen, Kongsberg and Kristiansand to allow for

improvements in journey time.



corridor (the Day Train from Oslo to Stavanger and back to Oslo, referred to as service “051c” in





assumed to operate every 2 hours. Please note that the scale differs from one Figure to another.

As with the Oslo – Bergen corridor, it can be seen that, in the section nearest to Oslo, the train is

relatively lightly loaded, with a marked increase in passengers boarding at Drammen and a

markedly higher level of demand beyond there, although declining towards Stavanger. The same

pattern is apparent in the reverse direction of travel.

The peak level of passengers carried in Scenario A in 2024 is of the order of 900 per day, rising

to around 1,100 with the improved journey time offered in Scenario B.

Figure 4.16 – Scen A (2024) Stavanger Daily Demand Profile



Figure 4.17 – Scen B (2024) Stavanger Daily Demand Profile


The pattern of total demand within the Oslo – Stavanger corridor is summarised in the following

Table 4.19 for both the modelled years. The rail element of this demand is further analysed in the

following section.

It may be observed that the modal shift exhibited by NTM5B in response to this improved rail

journey time, even at the corridor level, is relatively modest. The change in modal shift from 2024

to 2043 is even more modest. This is to be anticipated as the NTM5B model does not take

account of any congestion that may be experienced on road or rail travel; it is assumed that the

small increase in the car share is driven by assumptions on costs and values of time, as the LoS

data is held constant over time.


Scen A: 2024 Scen A: 2043


Car 42163 6229 15% 56983 7517 13%

Bus 3473 545 16% 4515 647 14%

Boat 42 5 12% 51 6 11%

Train 4695 1130 24% 6125 1335 22%

Air 3450 2509 73% 4437 3109 70%

Total 53823 10418 19% 72109 12614 17%

Mode Share

Car 78% 60%

79% 60%

Bus 6% 5%

6% 5%

Boat 0% 0%

0% 0%

Train 9% 11%

8% 11%

Air 6% 24%

6% 25%

Total 100% 100%

100% 100%



Scen B2: 2024 Scen B2: 2043


Car 42067 6216 15% 56853 7502 13%

Bus 3461 544 16% 4500 646 14%

Boat 41 5 12% 50 6 11%

Train 5006 1213 24% 6542 1436 22%

Air 3433 2499 73% 4414 3097 70%

Total 54008 10477 19% 72359 12686 18%

Mode Share

Car 78% 60%

79% 59%

Bus 6% 5%

6% 5%

Boat 0% 0%

0% 0%

Train 9% 12%

9% 11%

Air 6% 24%

6% 25%

Total 100% 101%

100% 101%


Table 4.20 shows more detailed results for rail passenger demand in the Oslo – Stavanger

corridor providing a breakdown between end-to-end trips and journeys to/from intermediate

areas.




versa) is not significant, at less than 10% of all rail trips.

Table 4.20 – Rail demand by trip type and exogenous growth (Scenario A 2024 to 2043)

Scen A: 2024 Scen A: 2043 Growth over 2024


Oslo Stavanger 166 40 231 50 39% 24%

Stavanger Oslo 166 40 231 50 39% 24%

Oslo Corridor 1837 470 2385 553 30% 18%

Corridor Oslo 1837 470 2385 553 30% 18%

Stavanger Corridor 77 14 103 17 33% 20%

Corridor Stavanger 77 14 103 17 33% 20%



Oslo-Stavanger as share

7% 7% 8% 7%



(31%).



Table 4.21 – Growth over Scenario A – Scenario B2

Scen B2: 2024 Scen B2: 2043


Oslo Stavanger 24% 31% 24% 31%

Stavanger Oslo 24% 31% 24% 31%



Stavanger Corridor 11% 13% 11% 13%

Corridor Stavanger 11% 13% 11% 13%



4.7.2 Scenario C (Stopping at Drammen, Porsgrunn, Arendal and Kristiansand)




end journey time savings.

Table 4.22 below presents a summary of the overall demand results for a Scenario C option

between Stavanger and Oslo via Kristiansand, assuming intermediate stops at Drammen,

Porsgrunn, Arendal and Kristiansand.

Table 4.22 – Summary of HSR Demand and Revenue: Scenario C Oslo –Stavanger (via Drammen,

Porsgrunn, Arendal, Kristiansand) 2024










It can be seen that annual HSR journeys in 2024 are estimated at 1.3 million, averaging around

3,600 per day. This demand breaks down as 64% business journeys, and 36% leisure journeys.

Total annual HSR revenue is estimated at approximately 0.7 NOK billion, with an average (one

way) yield of 600 NOK per journey for business, and 500 NOK for leisure.





Table 4.23 – HSR Demand by Origin/Destination type: Scenario C Oslo –Stavanger (via Drammen,

Porsgrunn, Arendal, Kristiansand) 2024

Oslo-Stavanger Annual Total (k) Business (k) Leisure (k)

Oslo/Akershus - Stavanger 200 100 100


Stavanger - Intermediate area 150 100 50


Stavanger - Other HSR corridors 100 100 50

Other 250 200 100

Total 1300 850 450

Table 4.23 shows that end-to-end journeys account for only 16% of all trips, ranging between

14% of leisure trips and 20% of business trips.

A further 39% of trips are between Greater Oslo and intermediate areas, with 25% between

Greater Oslo and other HSR corridors. Some within the category are journeys to/from zones in

the Bergen corridor, with access to HSR via the intermediate station Drammen. If the Bergen

corridor were provided as well as the Bergen corridor, these trips would fall away significantly.

Table 4.24 – Boardings by station: Scenario C Oslo –Stavanger (via Drammen, Porsgrunn, Arendal,

Kristiansand) 2024


Oslo S 1.1 31% 1.1

Drammen 0.2 5% 1.3

Porsgrunn 0.1 3% 1.4

Arendal 0.3 8% 1.7

Kristiansand 0.6 15% 2.3

Stavanger 1.3 37% 3.6

Table 4.24 shows that boardings at two of the intermediate stations – Drammen and to a greater

extent Porsgrunn – represent only a small fraction of the overall market which produces a total of

around 3,600 boardings per day. Arendal and in particular Kristiansand represent a more

significant proportion of daily boardings, with boardings at Kristiansand nearly half the number at

Oslo.


C. Air accounts for 40% of the market for trips between Oslo and Stavanger, while HSR and car

travel have a lower share, capturing approximately a quarter of the market each.



Figure 4.18 – Mode Share: Scenario C Oslo – Stavanger via Drammen, Porsgrunn, Arendal,

Kristiansand 2024 (Oslo-Stavanger)


are disaggregated by previous mode, journey purpose, and originating county. With Stavanger

located within Rogaland county, it is clear from the chart that end-to-end air trips are the principal

source of abstracted demand, although there is significant abstraction from trips to Vest-Agder,

where Kristiansand is located.

Figure 4.19 – Highest abstraction of journeys: Scenario C Oslo –Stavanger (via Drammen, Porsgrunn,

Arendal, Kristiansand) 2024


HSR station boardings. There is a large proportion of demand centred on the cities of Oslo,

Kristiansand and Stavanger, and in the remainder of Aust and Vest-Agder, with lower demand

around the areas surrounding Oslo. There is relatively low demand originating from the county of

Vestfold, interchanging at the stations at Drammen and Porsgrunn.

24%

24%

40%

3%9%

HSR

Car

Air

Bus

Classic Rail

0

20000

40000

60000

80000

100000

120000

140000

160000





4.7.3 Scenario D (stopping at Porsgrunn and Kristiansand)






option between Stavanger and Oslo via Kristiansand, assuming intermediate stops at Porsgrunn

and Kristiansand. The range of demand shown is based on the various sensitivities tested. The

lowest demand shown is based on HSR fares equalling current air fares. The highest demand is

based on the sensitivity where HSR fares are assumed to equal current rail fares (60% of air

fares) and there is provision for a connecting service from Oslo Central to Gardermoen Airport. In

terms of revenue, the lowest revenue shown is based on HSR fares equalling rail fares and there

is no connection to Gardermoen, while the highest revenue corresponds to the option with HSR

fares equalling air fares and a connecting service from Oslo Central to Gardermoen Airport.



Table 4.25 – Summary of HSR Demand and Revenue: Scenario D Oslo – Stavanger (via Porsgrunn

and Kristiansand) 2024







HSR Total revenue 1000 – 1700 400 – 700

HSR revenue from Business travel 700 – 1200 500 – 800

HSR revenue from Leisure travel 300 – 400 300 – 500


averaging between 5,400 and 8,400 per day. Total rail trips on the corridor (both HSR and on

existing rail services) are forecast to be around 3.3m to 4.4m a year in 2024. This demand

breaks down as 66% business journeys, and 34% leisure journeys. Total annual revenue is

estimated at between 1.0 and 1.7 NOK billion, with an average (one way) yield of 500 to 800

NOK per journey for business and 300 to 500 NOK for leisure.



Table 4.26 – HSR Demand by Origin/Destination type: Scenario D Oslo – Stavanger (via Porsgrunn

and Kristiansand) 2024

Oslo-Stavanger via Porsgrunn, Kristiansand


Oslo/Akershus - Stavanger 400 – 500 250 – 300 150 – 200

Oslo/Akershus - Intermediate area 400 – 650 300 – 400 200 – 250

Stavanger - Intermediate area 200 – 250 150 – 150 50 – 75

Oslo/Akershus - Other HSR corridors 400 – 550 250 – 350 150 – 200

Stavanger - Other HSR corridors 100 – 350 50 – 200 50 – 150

Other 350 – 850 250 – 550 100 – 300

Total 1950 – 3100 1300 – 1900 700 – 1200

Table 4.26 shows that end-to-end journeys account for approximately a fifth (21%) of all trips,

ranging between 21% of business trips and 22% of leisure trips. A further 35% of trips are

between Greater Oslo and intermediate areas, with 25% between Greater Oslo and other HSR

corridors.



Table 4.27 – Boardings by station: Scenario D Oslo – Stavanger (via Porsgrunn and Kristiansand)

2024


Oslo 2.1 – 2.5 34 - 38% 2.1 – 2.5

Porsgrunn 0.3 – 0.3 5% 2.3 – 2.8

Kristiansand 0.9 – 1.4 17 - 19% 3.2 – 4.2

Stavanger 2.1 – 3.2 39 - 43% 5.4 – 7,4

Table 4.27 shows that the station at Porsgrunn attracts approximately a third of the daily

boardings as Kristiansand. Daily boardings at Porsgrunn constitute 5% of overall demand on a

corridor which produces a total of between 5,400 and 7,400 HSR boardings per day.

Figure 4.21 below shows the forecast mode shares for end-to-end trips in 2024 under this

Scenario.

Figure 4.21 – Mode Share: Scenario D Oslo – Stavanger via Porsgrunn and Kristiansand 2024 (Oslo-

Stavanger)


are disaggregated by previous mode, journey purpose and originating county. With Stavanger

located in Rogaland county, it is clear from the chart that end-to-end air trips are the principal

source of abstracted demand. With Kristiansand located in Vest-Agder, it can be seen that there

is significant abstraction from business air trips to Kristiansand. There is also abstraction from car

leisure trips between Oslo and Stavanger.

42%

20%

28%

3%7%

HSR

Car

Air

Bus

Classic Rail



Figure 4.22 – Highest abstraction of journeys: Scenario D Oslo – Stavanger (via Porsgrunn and

Kristiansand) 2024


HSR station boardings. The figure shows that there is an increase in demand around the station

at Porsgrunn, although this demand is relatively low when compared with that surrounding the

main cities of Oslo, Kristiansand and Stavanger.


0

50000

100000

150000

200000

250000




4.7.4 Stavanger Corridor Summary and Conclusions

The current route between Oslo and Stavanger via Kristiansand can be upgraded using

Scenarios B, C and D. A key enhancement in Scenario C is to redirect long distance services

along the Vestfold Line, which will be double-tracked as part of the InterCity enhancements. For

Scenario D a new alignment will be constructed between Drammen and Porsgrunn, with these

stations providing connectivity with the Vestfold Line, which serves several urban areas. The new

HSR line constructed as part of Scenario D will also follow the south coast providing direct

connections to towns such as Arendal.

For Scenario D the example test presented in the model for this corridor is with two intermediate

stations at Kristiansand and Porsgrunn. For this option the total HSR market is estimated to be

around 2.0 to 3.1m trips per year (5,400 – 7,400 per day) in 2024, with revenue of between 1.0

and 1.7bn NOK per year. Of the total HSR demand, 32% is generated, with 41% abstracted from

air and 19% from car. The total rail market on the corridor (HSR services and existing rail

services) is estimated to be around 3.3m to 4.4m trips a year in 2024.

In Phase 3, further refinement of the model is required to investigate the interaction between the

HSR services with local and regional services on the corridor, and to assess the impact of the

proposals in the InterCity Study for improving services to the west of Oslo. The model will need to

be enhanced to test the recommendations from the station location analysis in Subject 4, which

proposes a parkway station at Sandnes, and the relocation of the station in Kristiansand away

from the harbour.



4.8 Trondheim – Oslo corridor




4.8.1 Scenario B


the existing route to Trondheim via Gardermoen, Hamar, Lillehammer and Otta to allow for




corridor (the Day Train from Oslo to Trondheim and back to Oslo, referred to as service “021a” in






It can be seen that, in the section nearest to Oslo, the train is relatively lightly loaded, with a

marked increase in passengers boarding at Drammen and a markedly higher level of demand

between there and Trondheim, although decaying towards Trondheim. The same pattern is

apparent in the reverse direction of travel.


1,600 per day, rising to around 1,900 with the improved journey time offered in Scenario B.

Figure 4.24 – Scen A (2024) Trondheim Daily Demand Profile



Figure 4.25 – Scen B (2024) Trondheim Daily Demand Profile


The pattern of total demand within the Oslo – Trondheim corridor is summarised in the following


following section.



to 2043 is even more modest, but this is to be anticipated as the NTM5B model does not take







Car 32503 3602 11% 43065 4257 10%

Bus 2452 281 11% 3097 325 11%

Boat 198 21 11% 240 24 10%

Train 4034 869 22% 5125 1009 20%

Air 2781 1719 62% 3522 2095 59%

Total 41968 6492 15% 55048 7709 14%

Mode Share

Car 77% 55%

78% 55%

Bus 6% 4%

6% 4%

Boat 0% 0%

0% 0%

Train 10% 13%

9% 13%

Air 7% 26%

6% 27%

Total 100% 100%

100% 100%



Scen B3: 2024 Scen B3: 2043


Car 32408 3592 11% 42939 4245 10%

Bus 2441 280 11% 3084 324 11%

Boat 196 21 11% 238 23 10%

Train 4326 946 22% 5502 1101 20%

Air 2764 1711 62% 3500 2085 60%

Total 42134 6550 16% 55262 7779 14%

Mode Share

Car 77% 55%

78% 55%

Bus 6% 4%

6% 4%

Boat 0% 0%

0% 0%

Train 10% 15%

10% 14%

Air 7% 26%

6% 27%

Total 100% 100%

100% 100%


Table 4.29 shows more detailed results for rail passenger demand in the Oslo – Trondheim

corridor, providing a breakdown between end-to-end trips and journeys to/from intermediate

areas.




versa) is not so significant, at about 20% of all rail trips.

Table 4.29 – Rail Demand by Sector (Scenarios A and B3)

Scen A: 2024 Scen A: 2043 Growth Over

2024


Oslo Trondheim 357 85 483 104 35% 22%

Trondheim Oslo 357 85 483 104 35% 22%

Oslo Corridor 1415 318 1782 364 26% 15%

Corridor Oslo 1415 318 1782 364 26% 15%

Trondheim Corridor 114 18 142 21 25% 15%

Corridor Trondheim 114 18 142 21 25% 15%



Oslo-Trondheim as share

18% 20% 19% 21%



(24%).



Table 4.30 – Growth Over Scenario A – Scenario B3

Scen B3: 2024 Scen B3: 2043


Oslo Trondheim 18% 24% 18% 24%

Trondheim Oslo 18% 24% 18% 24%



Trondheim Corridor 5% 5% 5% 5%

Corridor Trondheim 5% 5% 5% 5%



4.8.2 Scenario C (stopping at Gardermoen, Hamar, Lillehammer, Otta)




end journey time savings.

Table 4.31 below presents a summary of the overall demand results for the Scenario C option

between Trondheim and Oslo, assuming intermediate stops at Gardermoen, Hamar, Lillehammer

and Otta.

Table 4.31 – Summary of HSR Demand and Revenue: Scenario C Oslo – Trondheim (via Gardermoen,

Hamar, Lillehammer and Otta) 2024










It can be seen that annual HSR journeys in 2024 are estimated at 1.5 million, averaging around

4,000 per day. This demand breaks down as 59% business journeys, and 41% leisure journeys.

Total annual revenue is estimated at 1.0 NOK billion, with an average (one way) yield of 800

NOK per journey for business and 500 NOK for leisure.





Table 4.32 – HSR Demand by Origin/Destination type: Scenario C Oslo – Trondheim (via Gardermoen,

Hamar, Lillehammer and Otta) 2024

Oslo-Trondheim Annual Total (k) Business (k) Leisure (k)

Oslo/Akershus - Trondheim 450 250 200


Trondheim - Intermediate area 75 50 25


Trondheim - Other HSR corridors 400 250 150

Other 350 200 150

Total 1500 850 600

Table 4.32 shows that end-to-end journey account for almost a third (31%) with similar

proportions for leisure and business trips. A further 17% of trips are between Greater Oslo and

intermediate areas, with 29% between Greater Oslo and other HSR corridors.

Table 4.33 – Boardings by station: Scenario C Oslo – Trondheim (via Gardermoen, Hamar,

Lillehammer and Otta) 2024


Oslo 1.1 28% 1.1

Gardermoen 0.7 18% 1.8

Lillehammer 0.1 1% 1.9

Hamar 0.05 1% 2.0

Otta 0.2 6% 2.2

Trondheim 1.9 46% 4.0

Table 4.33 shows that intermediate stations at Lillehammer and Hamar have relatively low

patronage. The stations at Gardermoen (18% of the overall market) and to a lesser extent Otta

(6% of the overall market) attract a number of daily boardings. The stations at either end of the

corridor attract a combined total of 74% of a market which produces around 4,000 HSR

boardings per day.


C. HSR accounts for a third of the modal share, with car and air accounting for a further quarter

each.



Figure 4.26 – Mode Share: Scenario C Oslo – Trondheim via Gardermoen, Hamar, Lillehammer and

Otta 2024 (Oslo/Akershus-Trondheim)


are disaggregated by previous mode, journey purpose and originating county. With Trondheim

located in Sør-Trondelag county, it is clear from the chart that end-to-end air trips are the

principal source of abstracted demand, particularly business trips.

Figure 4.27 – Highest abstraction of journeys: Scenario C Oslo – Trondheim (via Gardermoen, Hamar,

Lillehammer and Otta) 2024

Figure 4.28 provides a GIS presentation of the spatial pattern of annual HSR trip-ends, and daily

HSR station boardings. The majority of demand is centred in Trondheim and the areas

surrounding the city. There is also large demand from the bydeler of Oslo and from Gardermoen

Airport. It can also be seen that the demand for stations at Lillehammer and Hamar is minimal in

this option, with a station at Otta proving slightly more popular.

33%

26%

26%

4%

11%

HSR

Car

Air

Bus

Classic Rail

0

50000

100000

150000

200000

250000







4.8.3 Scenario D (with stop at Gardermoen)






option between Trondheim and Oslo, assuming an intermediate stop at Gardermoen. The range

of demand shown is based on the various sensitivities tested. The lowest demand shown is

based on HSR fares equalling current air fares. The highest demand is based on the sensitivity

where HSR fares are assumed to equal current rail fares (60% of air fares). In terms of revenue,

the lowest revenue shown is based on HSR fares equalling rail fares, while the highest revenue


Table 4.34 – Summary of HSR Demand and Revenue: Scenario D Oslo – Trondheim (via Gardermoen)

2024












journeys, and 39% leisure journeys. Total annual revenue is estimated at between0.9 and 1.3

NOK billion, with an average (one way) yield of 500 to 800 NOK per journey for business and 300

to 500 NOK for leisure. Total rail demand on the corridor is forecast to be around 2.8m to 3.2m

trips per year in 2024.



Table 4.35 – HSR Demand by Origin/Destination type: Scenario D Oslo – Trondheim (via Gardermoen)

2024

Oslo-Trondheim via Gardermoen


Oslo/Akershus - Trondheim 650 – 800 400 – 450 250 – 350

Oslo/Akershus - Intermediate area 250 – 300 150 – 175 100 – 150

Trondheim - Intermediate area 25 – 50 25 – 50 0 - 25


Trondheim - Other HSR corridors 550 – 650 300 – 350 200 – 250

Other 350 – 450 200 – 250 125 – 150

Total 1800 – 2200 1100 – 1300 700 – 900



Table 4.41 shows that end-to-end journeys account for just over a third (35%) of all trips, ranging

with little difference in the proportion for business and leisure trips. A further 13% of trips are

between Greater Oslo and intermediate areas, with 30% between Trondheim and other HSR

corridors.

Table 4.36 – Boardings by station: Scenario D Oslo – Trondheim (via Gardermoen) 2024


Oslo 1.4 – 1.8 29 - 30% 1.4 – 1.8

Gardermoen 1.0 – 1.2 20 - 21% 2.5 – 3.1

Trondheim 2.5 – 3.0 50% 4.9 – 6.1

Table 4.36 shows that intermediate station at Gardermoen attracts 20% of overall demand within

a corridor which produces a total of between 4,900 and 6,100 HSR boardings per day. The

majority of the trips from Gardermoen are in addition to those made from Oslo, rather than

abstracted. Hence the overall demand is far higher than there would be for a non-stop option.


D. HSR makes up almost half of the demand, with car and air attracting approximately as much

again, in roughly equal measure. There is still a sizable proportion (10%) of classic rail demand.

Figure 4.29 – Mode Share: Scenario D Oslo – Trondheim via Gardermoen 2024 (Oslo/Akershus-

Trondheim)


are disaggregated by previous mode, journey purpose and originating county. With Trondheim

located in Sør-Trondelag county, it is clear from the chart that end-to-end air trips are the

principal source of abstracted demand. There is abstraction also from Nord-Trondelag for air trips

to Oslo.

43%

23%

20%

4%

10%

HSR

Car

Air

Bus

Classic Rail



Figure 4.30 – Highest abstraction of journeys: Scenario D Oslo – Trondheim (via Gardermoen) 2024


HSR station boardings. There is slightly higher demand in intermediate areas, particularly in the

county of Akershus. There is still significant demand from the regions surrounding Trondheim

accessing the HSR station to travel to Oslo.

0

50000

100000

150000

200000

250000

300000

350000







4.8.4 Trondheim Corridor Summary and Conclusions

The existing route to Trondheim via Gardermoen, Hamar, Lillehammer and Otta can be upgraded

using Scenarios B, C or D. For Scenario D, the example shown has one intermediate station at

Gardermoen Airport. For this option, the total HSR market is around 1.8 to 2.2m trips per year

(4,900 – 6,100 daily) in 2024, with revenue of between 0.9 and 1.3bn NOK per year. Of this

demand, 22% is generated, with 62% abstracted from air and 11% from car. The total rail market,

including existing rail services, is forecast to be around 2.8m to 3.2m trips a year in 2024.

A key consideration for Phase 3 will be to analyse the benefits or disbenefits of constructing a

more direct alignment between Gardermoen for Trondheim, which would not be able to serve

Hamar, Lillehammer or Otta for connections to towns such as Ǻlesund and Kristiansand on the

north coast, but would reduce end-to-end journey times between Oslo and Trondheim. Another

consideration for Phase 3 would be to extend the HSR route from Trondheim Central to Værnes

Airport, to improve connectivity with the airport and to better serve towns in Nord-Trondelag.



4.9 Oslo – Stockholm corridor




4.9.1 Scenario B


the existing route to Stockholm via Lillestrøm, Kongsvinger, and Karlstad to allow for




corridor (the day train from Oslo to Stockholm and back to Oslo, referred to as service “011b” in






It can be seen that, in the section nearest to Oslo, the train is very lightly loaded, although with a

marked increase in passengers boarding at Lillestrom and a markedly higher level of demand

between there and Stockholm. The same pattern is apparent in the reverse direction of travel. It

should be borne in mind that there is no representation of cross-border demand in NTM5B, and

hence these results significantly understate potential demand. However, the low level of

incremental change suggests that overall passenger numbers – including cross-border travel –

would not increase significantly in Scenario B.


only 25 per day; not rising with the improved journey time offered in Scenario B.

Figure 4.32 – Scen A (2024) Stockholm Daily Demand Profile



Figure 4.33 – Scen B (2024) Stockholm Daily Demand Profile


The pattern of total demand within the Oslo – Stockholm corridor is summarised in the following


following section.







Table 4.37 – Corridor Demand by Mode and Purpose



Car 1503 251 17% 1978 294 15%

Bus 136 26 19% 170 30 17%

Boat 0 0 - 0 0 -

Train 173 45 26% 211 50 24%

Air 0 0 - 0 0 -

Total 1812 322 18% 2359 373 16%

Mode Share

Car 83% 78% 84% 79%

Bus 8% 8% 7% 8%

Boat 0% 0% 0% 0%

Train 10% 14% 9% 13%

Air 0% 0% 0% 0%

Total 100% 100% 100% 100%



Scen B4: 2024 Scen B4: 2043


Car 1503 251 17% 1978 294 100%

Bus 136 26 19% 170 30 100%

Boat 0 0 - 0 0 -

Train 173 45 26% 212 50 100%

Air 0 0 - 0 0 -

Total 1812 322 18% 2359 373 100%

Mode Share

Car 83% 78%

84% 79%

Bus 8% 8%

7% 8%

Boat 0% 0%

0% 0%

Train 10% 14%

9% 13%

Air 0% 0%

0% 0%

Total 100% 100%

100% 100%

Pattern of Rail Demand

Table 4.38 shows more detailed results for rail passenger demand in the Oslo – Stockholm

corridor for both the modelled years, although all the numbers are very small. This results from

the lack of cross-border demand in NTM5B, as already mentioned.

It may be observed that there is a forecast increase on rail demand in the corridor of up to 21%

between the two modelled years, although less for work purpose trips, implying a greater relative

growth in other purposes (e.g. leisure).

There is no evidence of growth in rail demand, as a result of the improved journey time offered in

Scenario B. This is caused by the very low levels of demand in this corridor.

Table 4.38 – Rail Demand by Sector (Scenarios A and B5)

Scen A: 2024 Scen A: 2043 Growth Over 2024


Oslo Stockholm 0 0 0 0 - -

Stockholm Oslo 0 0 0 0 - -

Oslo Corridor 83 22 101 24 21% 10%

Corridor Oslo 83 22 101 24 21% 10%

Stockholm Corridor 0 0 0 0 - -

Corridor Stockholm 0 0 0 0 - -

Corridor Corridor 0 0 0 0 - -


Oslo-Stockholm as share

0% 0% 0% 0%



Table 4.39 – Growth over Scenario A – Scenario B5

Scen B5: 2024 Scen B5: 2043


Oslo Stockholm - - - -

Stockholm Oslo - - - -



Stockholm Corridor - - - -

Corridor Stockholm - - - -

Corridor Corridor - - - -


4.9.2 Scenario C (with stops at Lillestrøm and Kongsvinger)



are likely, „short cutting‟ circuitous sections of the existing route and resulting in larger end-to-end

journey time savings.

Table 4.40 below presents a summary of the overall demand results for the Scenario C option

between Stockholm and Oslo, assuming intermediate stops at Lillestrøm and Kongsvinger.

Table 4.40 – Summary of HSR Demand and Revenue: Scenario C Oslo – Stockholm (via Lillestrøm

and Kongsvinger) 2024










It can be seen that annual journeys in 2024 are estimated at 0.7 million, averaging around 2,000

per day. This demand breaks down as 30% business journeys and 70% leisure journeys. Total

annual revenue is estimated at 0.5 NOK billion, with an average (one way) yield of 800 NOK per

journey for business and 600 NOK for leisure.





Table 4.41 – HSR Demand by Origin/Destination type: Scenario D Oslo – Stockholm (via Lillestrøm

and Kongsvinger) 2024

Oslo-Stockholm Annual Total (k) Business (k) Leisure (k)

Oslo/Akershus - Stockholm 700 200 500

Oslo/Akershus - Corridor 0 0 0

Stockholm - Corridor 2 0 0

Oslo/Akershus - Other corridors 25 25 0

Stockholm- Other corridors 0 0 0

Other 0 0 0

Total 750 200 500

Table 4.41 shows that end-to-end journey account for almost all (93%) trips, ranging between

87% of business trips and 96% of leisure trips. A further 4% of trips are between Greater Oslo

and other HSR corridors.

Table 4.42 – Boardings by station: Scenario C Oslo – Stockholm (via Lillestrøm and Kongsvinger)

2024


Oslo S 0.5 25% 0.5

Lillestrøm 0.5 26% 1.0

Kongsvinger 0.05 2% 1.1

Stockholm 1.0 47% 2.0

Table 4.42 shows that the intermediate station at Lillestrøm attracts roughly one quarter (26%) of

overall demand for a corridor which produces a total of around 2,000 HSR boardings per day. A

stop at Kongsvinger attracts a mere 2% of demand.


D. HSR accounts for nearly half (46%) of overall demand, with car taking about a fifth (21%) and

air about a third (31%).

Figure 4.34 – Mode Share: Scenario C Oslo – Stockholm via Lillestrøm and Kongsvinger 2024

(Oslo/Akershus-Stockholm)

46%

21%

31%

1%

HSR

Car

Air

Bus

Classic Rail




are disaggregated by previous mode, journey purpose and originating county. It is clear from the

chart that end-to-end air trips are the principal source of abstracted demand.

Figure 4.35 – Highest abstraction of journeys: Scenario C Oslo – Stockholm (via Lillestrøm and

Kongsvinger) 2024

4.9.3 Scenario D (stopping at Lillestrøm)



limit train speeds. This will allow for a very significant reduction in journey time and an increase in

the frequency of rail services.


option between Stockholm and Oslo, with an intermediate stop at Lillestrøm. The range of

demand shown is based on the various sensitivities tested. The lowest demand shown is based

on HSR fares equalling current air fares. The highest demand is based on the sensitivity where

HSR fares are assumed to equal current rail fares (60% of air fares. In terms of revenue, the

lowest revenue shown is based on HSR fares equalling rail fares, while the highest revenue


0

10000

20000

30000

40000

50000

60000

70000

80000

90000




Table 4.43 – Summary of HSR Demand and Revenue: Scenario D Oslo – Stockholm (via Lillestrøm)

2024










It can be seen that annual HSR journeys in 2024 are estimated at between 0.8 and 1.0 million,




to 600 NOK for leisure.



Table 4.44 – HSR Demand by Origin/Destination type: Scenario D Oslo – Stockholm (via Lillestrøm)

2024

Oslo-Stockholm Annual Total (k) Business (k) Leisure (k)

Oslo/Akershus - Stockholm 800 – 1000 200 – 250 550 – 7250


Stockholm - Corridor 0 0 0


Stockholm- Other corridors 0 – 25 0 0

Other 0 0 0

Total 800 – 1050 250 – 300 550 – 750

Table 4.44 shows that end-to-end journey account for almost all (95%) trips.

Table 4.45 – Boardings by station: Scenario D Oslo – Stockholm (via Lillestrøm) 2024


Oslo S 0.6 – 0.7 25% 0.6 – 0.7

Lillestrøm 0.6 – 0.8 27 - 28% 1.2 – 1.5

Stockholm 1.1 – 1.4 48% 2.3 – 2.8

Table 4.45 shows that demand is split roughly equally between the Oslo and the stop at

Lillestrøm, which serves the east of Oslo. The overall HSR demand is approximately 2,300 to

2,800 boardings per day.


D. HSR attracts half of the demand, with air attracting 28% and car 20%.



Figure 4.36 – Mode Share: Scenario D Oslo – Stockholm via Lillestrøm 2024 (Oslo/Akershus-

Stockholm)


are disaggregated by previous mode, journey purpose and originating county. The chart shows

that demand is principally abstracted from air travel, particularly leisure.

Figure 4.37 – Highest abstraction of journeys: Scenario D Oslo – Stockholm (via Lillestrøm) 2024

51%

20%

28%

1%

HSR

Car

Air

Bus

Classic Rail

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000




4.9.4 Stockholm Corridor Summary and Conclusions

The existing route to Stockholm via Lillestrøm, Kongsvinger and Karlstad can be upgraded using

Scenarios B, C or D. A key infrastructure enhancement for Scenario D would be to construct a

new, more direct line between Lillestrøm and Karlstad, significantly reducing journey times. For

Scenario D the example option presented has an intermediate stop at Lillestrøm only, to provide

connectivity with the east of Oslo and Gardermoen Airport. For this option, the total HSR market

is between 0.8 and 1.0m trips per year (2,300 – 2,800 daily) in 2024 with revenue of around 0.4

to 0.6bn NOK per year. Of the demand for HSR, 40% is generated, with 51% abstracted from air

and 8% from car.

For Phase 3 it is suggested that a stop at Gardermoen Airport is tested instead of Lillestrøm as

there is currently only a marginal case for an intermediate station at Lillestrøm. The model will

also need to be refined with passenger count data for cross-border trips to Sweden, as well as

trips between Karlstad and Stockholm, in order to more accurately model the demand potential

on this corridor.



4.10 Oslo – Gothenburg corridor




4.10.1 Scenario B


the existing route to Gothenburg via Ski, Moss, Sarpsborg and Halden to allow for improvements

in journey time.



corridor (the day train from Oslo to Gothenburg and back to Oslo, referred to as service “001b” in






It can be seen that, over most of the route, the train is relatively lightly, if evenly, loaded. This is

mainly because NTM5B does not represent cross-border journeys – hence actual figures are

likely to be significantly higher. The same pattern is apparent in the reverse direction of travel.


only 300 per day, rising insignificantly with the improved journey time offered in Scenario B.

Figure 4.38 – Scen A (2024) Gothenburg Daily Demand Profile



Figure 4.39 – Scen B (2024) Gothenburg Daily Demand Profile


The pattern of total demand within the Oslo – Gothenburg corridor is summarised in the following


following section.










Car 5107 1202 24% 6984 1468 21%

Bus 611 99 16% 803 118 15%

Boat 0 0 - 0 0 -

Train 900 226 25% 1175 267 23%

Air 0 0 - 0 0 -

Total 6618 1528 23% 8962 1854 21%

Mode Share

Car 77% 79%

78% 79%

Bus 9% 6%

9% 6%

Boat 0% 0%

0% 0%

Train 14% 15%

13% 14%

Air 0% 0%

0% 0%

Total 100% 100%

100% 100%



Scen B4: 2024 Scen B4: 2043


Car 5105 1202 24% 6982 1468 21%

Bus 611 99 16% 803 118 15%

Boat 0 0

0 0

Train 906 228 25% 1184 270 23%

Air 0 0

0 0

Total 6623 1529 23% 8969 1856 21%

Mode Share

Car 77% 79%

78% 79%

Bus 9% 6%

9% 6%

Boat 0% 0%

0% 0%

Train 14% 15%

13% 15%

Air 0% 0%

0% 0%

Total 100% 100%

100% 100%

Pattern of Rail Demand

Table 4.47 shows more detailed results for rail passenger demand in the Oslo – Gothenburg

corridor for both the modelled years.

It may be observed that there is a forecast increase on rail demand in the corridor of up to 30%

between the two modelled years, although less for work purpose trips, implying a greater relative

growth in other purposes (e.g. leisure). For both work purpose trips and total trips, the end to end

patronage (Oslo to Gothenburg or vice versa) is fairly significant, at nearly 20% of all rail trips.

However, many of the elements in this Table are quite small, reflecting the nature of the corridor

and lack of cross-border demand in NTM5B

The growth in rail demand, as a result of the improved journey time offered in Scenario B, is

minimal, however. Any growth in this corridor would have to come from cross-border demand,

which is not included in NTM5B.

Table 4.47 – Rail Demand by Sector

Scen A: 2024 Scen A: 2043 Growth Over 2024


Oslo Gothenburg 0 0 0 0 - -

Gothenburg Oslo 0 0 0 0 - -

Oslo Corridor 446 113 583 133 31% 18%

Corridor Oslo 446 113 583 133 31% 18%

Gothenburg Corridor 0 0 0 0 - -

Corridor Gothenburg 0 0 0 0 - -



Oslo-Gothenburg as share

0% 0% 0% 0%



Table 4.48 – Growth Over Scenario A – Scenario B4

Scen B4: 2024 Scen B4: 2043


Oslo Gothenburg - - - -

Gothenburg Oslo - - - -



Gothenburg Corridor - - - -

Corridor Gothenburg - - - -



4.10.2 Scenario C (with stops at Ski, Moss, Sarpsborg, Halden)

For Scenario C an example test has not been possible due to the current lack of sensitivity in the

model to intermediate stations on this route within Norway. This is due to the absence of trips of

less than 100km in the base demand matrices. This issue will be addressed in Phase 3 through

the sourcing of specific demand data for this corridor.

4.10.3 Scenario D (non-stop)






option between Gothenburg and Oslo, assuming no intermediate stops. The range of demand



are assumed to equal current rail fares (60% of air fares). In terms of revenue, the lowest

revenue shown is based on HSR fares equalling rail fares, while the highest revenue


Table 4.49 – Summary of HSR Demand and Revenue: Scenario D Oslo – Gothenburg (non-stop) 2024





HSR Passenger kilometres (million) 100 - 200 0.4 – 0.5





It can be seen that annual HSR journeys in 2024 are estimated at between 0.8 and 1.0 million,




to 500 NOK for leisure. Total rail trips on the corridor – including those still travelling on existing



rail services as well as the HSR services – are forecast to be around 1.2m to 1.3m trips per year

in 2024.



Table 4.50 – HSR Demand by Origin/Destination type: Scenario D Oslo – Gothenburg (non-stop) 2024

Oslo-Gothenburg Annual Total (k) Business (k) Leisure (k)

Oslo/Akershus - Gothenburg 850 – 1000 650 – 750 150 – 250


Gothenburg - Corridor 0 0 0


Gothenburg - Other corridors 0 0 0

Other 0 0 0

Total 850– 1000 650 – 750 150 – 250

Table 4.50 shows that end-to-end journey account for almost all (99%) trips.

Table 4.51 – Boardings by station: Scenario D Oslo – Gothenburg (non-stop) 2024


Oslo S 1.1 – 1.4 50% 1.1 – 1.4

Gothenburg 1.1 – 1.4 50% 2.3 – 2.7

Table 4.51 shows that demand is split equally between the two termini stations as part of the total

of 2,300 to 2,700 HSR boardings per day.


D. HSR has just over 40% share of the demand, while the other 60% share is taken by car travel.

Figure 4.40 – Mode Share: Scenario D Oslo – Gothenburg non-stop 2024 (Oslo/Akershus-

Gothenburg)


are disaggregated by previous mode, journey purpose and originating county. It is clear that

almost all of the HSR demand is abstracted from end-to-end car trips.

42%

58%

0%

HSR

Car

Air

Bus

Classic Rail



Figure 4.41 – Highest abstraction of journeys: Scenario D Oslo – Gothenburg (non-stop) 2024

4.10.4 Gothenburg Corridor Summary and Conclusions

The existing route to Gothenburg via Ski, Moss, Fredrikstad, Sarpsborg and Halden can be

upgraded using Scenarios B, C or D. It should be noted that this corridor is a very different

market to the other Oslo corridors as it is dominated by car, with up to 3m cross-border trips per

year. Currently, the data made available has not been sufficient enough to accurately model the

demand between intermediate stations, such as Sarpsborg and Halden, as the majority of trips in

the Østfold area are under 100km in length.

The option tested for Scenario D therefore runs non-stop from Oslo to Gothenburg. This option is

forecast to attract between 0.8 and 1.0m trips per year by HSR (2,300 – 2,700 daily), generating

0.5 to 0.7bn NOK of revenue per year. Of this demand 32% is generated, with 67% abstracted

from car and only 1% from air, indicating the differing trends on this corridor. Around 1.2m to

1.3m total rail trips per year (both HSR and classic rail) are forecast on the corridor in 2024.

For Phase 3 it will be necessary to refine the model by including passenger counts for cross-

border trips between Norway and Sweden. In addition, a detailed analysis of short distance

journeys in the area will be required to determine potential stations in Norway, which are driven

by the commuter market to Oslo. There will be a significant overlap between HSR services and

improvements from the InterCity study.

0

50000

100000

150000

200000

250000




5 Conclusions 5.1 Introduction

This section provides a summary of the key findings from the analysis of the current travel market

in Norway, the discussion of the future market growth assumptions, and the demand and

revenue forecasting. Recommendations for future work to be carried out in Phase 3 of the HSR

study are also presented.

We emphasise that the findings of this report only reflect Stage 2 of the overall High Speed Rail

Assessment project, and are designed to assist in the more detailed assessment during Phase 3

of the project. In particular, we emphasise that market analysis is only one of many interacting

factors affecting the viability of high speed rail in Norway –elements of costs, environmental and

economic effects are equally important.

5.2 Summary of Current Travel Markets

The size of the potential market for HSR in Norway is much smaller than the HSR markets

already established in countries such as France and Germany, but similar to that of Sweden.

From experience in other European countries where HSR is already well established, there has

been almost total abstraction from air on routes served by HSR as rail journey times have been

dramatically reduced and major rail stations are located more conveniently than the airports.

Business travel in Norway is dominated by air due to the relative speed and frequency of

services, and there is a higher value of time associated with these trips. Business travellers are

prepared to spend time accessing airports located outside city centres. Conversely, leisure travel

is more evenly spread between car, air and rail. For relatively short distance trips within corridors

of up to around 300km (e.g. Oslo-Kristiansand), car travel is dominant. . In part, this dominance

is due to leisure travellers placing higher importance on minimising monetary costs, combined

with the ability to travel as a group. Another factor is the convenience of access to a car when

making visits of extended duration - for out-of-town sightseeing, for example. Therefore, the key

market for potential HSR in Norway will be business travel, which is currently served by air.

However, HSR will look to abstract from the leisure market on long distance routes, in part

because the new mode may allow the possibility of out-and-back travel within a day, avoiding the

hotel costs associated with car use.

Comparison of the level of service for individual modes of public transport indicates that air travel

provides the best service for city-to-city travel, both in terms of service frequency and journey

time, which explains the high market share. HSR services tend to stop less frequently than

classic rail but city stations offer good connectivity with other modes of transport, including

classic (regional/local) rail. Therefore any potential HSR service in Norway would compete

mainly with city-to-city travel currently dominated by air, rather than travel within corridors. In

order to compete with air travel, HSR will need to offer a competitive service, in terms of

frequency, journey times, fares, accessibility and comfort.

5.3 Future (Do Minimum) Travel Market

Future year growth forecasts have been developed based upon demand matrices produced by

the NTM5 model. These future year matrices have been analysed to understand the growth

trends by mode for each corridor. It has been shown that between the largest cities:

Business passengers today predominantly use air over long distances and, in the Do

Minimum scenario, this is reinforced over the next fifty years with the highest unconstrained

growth experienced by this mode;

On the Oslo-Bergen corridor, volumes of rail business trips are forecast to grow significantly,

although this is due to higher base demand, rather than a faster percentage growth rate;



Overall, over the 50 year period, leisure experiences higher growth than business;

Growth in Do Minimum leisure passengers is focussed on car journeys;

Measured in absolute volumes, growth in car journeys is high on all corridors for leisure

travel, but negligible for business (except on the Bergen-Stavanger corridor where car is

competitive with air overall);

Growth rates on all modes are higher than the underlying population growth rate, particularly

for leisure travel indicating that greater incomes in the future will lead to increased trips;

On most corridors, the growth rate of business travel is typically higher in the period to 2020

than the 40 years (2021-2060) that follow;;

Classic rail travel will continue to be dominated by leisure users, with an increase from 79%

to 83% in the share of trips undertaken by leisure users. Conversely, business users‟ share

of air travel falls from 61% to 56%;

In order to optimise the HSR business case, it seems appropriate to target business travellers

who currently fly, and leisure travellers who currently fly or drive. In the latter case, discounts

for group/family travel may be worthwhile.

5.4 Commentary on demand and revenue forecasts

5.4.1 Context of forecasts

There are several general observations that can be applied across all corridors, relating to the

trends in HSR demand and the performance of the demand and revenue forecasting model:

Demand forecasts are roughly comparable to those in the previous study conducted by VWI.

However, we emphasise that the forecasts in this report have been constructed completely

independently – and represent different scenarios for HSR in terms of stopping patterns,

journey times, service frequencies and fares. Another key difference is that we understand

the VWI forecasts encompass all rail services, whereas the forecasts in this report separate

HSR and classic rail.

The demand and revenue forecasts in this work represent outputs from the forecasting

models based on example development scenarios. Much more optimisation work will be

needed in Phase 3 around the specifications which could increase or decrease demand and

revenue figures significantly. This optimisation work will also include taking into account cost

figures, economic benefits and environmental effects.

The potential for intermediate stops is especially evident on the Oslo – Kristiansand –

Stavanger corridor and the Oslo – Gothenburg corridor where there is relatively high

population density. There are strong interactions with the parallel JBV Intercity study,

particularly in relation to the market for travel into Oslo of less than 100km, which is

specifically excluded from this work and the forecasting results. Developing options which

could serve both the long-distance and inter-city markets into Oslo could significantly improve

demand and revenue case for options.

5.4.2 Common findings

A key trend for all corridors – with the notable exception of the Oslo – Gothenburg corridor – is

that most of the demand for HSR is abstracted from air. This means that there is a strong

demand and revenue case for adopting Scenario D – with the most aggressive reductions in end-

to-end journey times – along each of the main corridors. At the other extreme, once journey times

are reduced sufficiently, there is a diminishing market return for reducing journey times further,

which may improve the case for intermediate stations. This issue is examined in more detail in

the separate Subject 4 report.



The relatively small increases in rail demand for Scenario B over Scenario A show that there

might be a case for some incremental improvements in journey times, but that these

interventions do not cause a major shift away from air on those corridors – increases in travel by

rail are more incremental, as would be expected.

Results on the Trondheim corridor demonstrate there is likely to be strong case for linking all

corridors directly to Gardermoen Airport, This is particularly relevant for the domestic HSR

corridors to Bergen, Stavanger and Kristiansand, where overall HSR demand could be increased

significantly. There is also potential for optimising connections with other key airports in Phase 3,

such as an extension of HSR from Trondheim Central Station to Værnes Airport.

5.4.3 Corridor Analysis

This section presents a summary of the HSR impacts on the corridors tested, across each of the

scenarios. This comparison will enable an initial judgement as to what scale of improvement is

viable on each corridor. Further refinement of the demand forecasting model will be required in

Phase 3 to determine the optimal stopping pattern for Scenarios C and D, in particular for station

stops within city areas, which may alter the demand significantly. There will also be greater

distinction between the different HSR route alignments, taking into account the varying lengths

and speed characteristics of the respective routes.

Table 5.1 presents a comparison of the demand per day for HSR on each corridor under each

scenario. Universally, Scenario D on each corridor results in the highest levels of demand as

measured by passenger trips.

It can be seen that for Scenario C across the corridors under consideration, Oslo – Trondheim is

the corridor with the highest patronage, presumably due in part to demand for Gardermoen

Airport. Oslo – Kristiansand – Stavanger performs relatively poorly when considering the higher

density of population along the route; however, this may be due to the higher end-to-end journey

time. Figures would be expected to increase significantly if the line also served the Intercity

commuting market into Oslo.

For Scenario D, the Oslo – Bergen/Stavanger route via Haukeli attracts the most HSR trips,

which is unsurprising as it connects three major urban centres in Norway. The next most popular

route is Oslo – Kristiansand – Stavanger corridor; again an expected result as it serves the south

coast, which has a relatively high population density. The route has higher demand than

Trondheim in Scenario D as the journey time saving is higher between the two scenarios (i.e. 3

hours compared with 1 hour 45 minutes). Either of these two routes could be combined with the

Stavanger – Bergen route to further increase HSR patronage.

Scenario B provides a slight increase in rail patronage (compared to Scenario A) on the Oslo –

Bergen corridor and the Oslo – Kristiansand / Stavanger corridors, but nowhere near the new

HSR patronage achieved by Scenarios C and D. For the corridors into Sweden, where relatively

little travel is in the NTM5 model (only domestic demand of 100km or more from Oslo is

included), the demand effects are negligible.



Table 5.1 – HSR Demand per Day by Corridor for Each Scenario (2024)

Route Passengers per day (2024) 000's40

Scenario A Scenario B Scenario C Scenario D

Oslo – Bergen 2.8 3.6 3.1 4.2 – 6.8

Oslo – Bergen/Stavanger (“Haukeli”) - - - 6.8 – 11.3

Stavanger – Bergen - - - 2.0 – 2.5

Oslo – Kristiansand – Stavanger 4.7 5.0 3.6 5.4 – 8.4

Oslo – Trondheim 4.0 4.3 4.0 4.9 – 6.1

Oslo – Stockholm 0.2 0.2 2.0 2.3 – 2.8

Oslo – Gothenburg 0.9 0.9 - 2.3 – 2.7

The corresponding demand per year is shown in Table 5.2.

Table 5.2 – HSR per Year by Corridor for Each Scenario (2024)

Route Passengers per year (2024) 000's

Scenario A Scenario B Scenario C Scenario D

Oslo – Bergen 1000 1300 1100 1500 – 2500

Oslo – Bergen/Stavanger (“Haukeli”)

- - - 2500 – 4100

Stavanger – Bergen - - - 700 – 900

Oslo – Kristiansand – Stavanger 1700 1800 1300 2000 – 3100

Oslo – Trondheim 1500 1600 1500 1800 – 2200

Oslo – Stockholm 100 100 700 800 – 1000

Oslo – Gothenburg 300 300 - 800 – 1000

Table 5.3 shows the average passengers per train for HSR in Scenarios C and D, on a typical

day. These figures are based on the levels of service shown earlier in the report in Table 4.2 (i.e.

60 minute headway for all corridors except Stavanger – Bergen, which has a 120 minute

headway) with the assumption of an 18 hour day.

40 Note that figures for Scenarios A and B represent overall rail demand on improved existing rail networks,

whereas Scenarios C and D represent HSR demand only, and exclude rail demand on the existing rail network.



Table 5.3 – Average HSR Demand per Train by Corridor for Scenarios C and D (2024)

Route Average passengers per train

Scenario C Scenario D

Oslo – Bergen 85 117 - 188

Oslo – Bergen/Stavanger (“Haukeli”) - 185 - 315

Stavanger – Bergen - 112 - 140

Oslo – Kristiansand – Stavanger 101 149 - 234

Oslo – Trondheim 112 137 - 169

Oslo – Stockholm 56 63 - 79

Oslo – Gothenburg - 63 - 76

The average loadings figures should be treated with caution, as there is inherent variation in

demand across the day. Comparable average load factors of around 40%-50% are achieved in

the UK but still encounter significant crowding during peak periods. Again, depending on fare and

other scenario assumptions, these figures could be significantly higher as options are developed

during Phase 3.

Table 5.4 presents the revenue forecasts for Scenarios C and D, under the current fare

assumptions. It can be seen that for Scenario C Trondheim has the highest revenue but for

Scenario D the highest revenue is for the Haukeli route to Bergen and Stavanger, with the

revenue for the Trondheim and Stavanger routes roughly similar.

Table 5.4 – HSR Revenue per Year for Scenarios C and D (2024)

Route Revenue per year (million NOK)

Scenario C Scenario D

Oslo – Bergen 701 744 - 1303

Oslo – Bergen/Stavanger (“Haukeli”) - 1510 - 2466

Stavanger – Bergen - 395 - 530

Oslo – Kristiansand – Stavanger 747 999 - 1667

Oslo – Trondheim 976 947 - 1290

Oslo – Stockholm 507 434 - 574

Oslo – Gothenburg - 479 - 671

Figure 5.1 shows the additional HSR journeys on each corridor under Scenario D, compared

against Scenario C. The results suggest that additional infrastructure investment to reduce

journey times may be most successful in delivering further HSR demand on the Stavanger and

Bergen corridors, with the least effect felt on the Trondheim and Stockholm corridors. A similar

picture emerges when this analysis is conducted in terms of revenue.



Figure 5.1 – Incremental HSR journeys by corridor Scenario D over Scenario C (2024 estimates,

percentage)

5.5 Recommendations for Phase 3

Phase 3 of the overall High Speed Rail Assessment project will take the demand and revenue

forecasting model and use it to assess and develop options in more detail. This option

development process will include interactions with other work from Phase 2, including

assessment of Finance and Economics (Contract 6), Technical and Safety Analysis (Contract 1)

and Rail Planning and Development (Contract 2), as well as the detailed alignment work being

undertaken in Phase 3.

This option development process will also take into account further development of the options to

maximise demand and revenue, including:

Changes to service assumptions including journey times, operating frequencies and stopping

patterns;

Refinement of overall option development, including potential interactions with the InterCity

market into Oslo and connections to Gardermoen Airport – a key market from Bergen and

Stavanger;

Consideration of potential impacts of responses from airlines and existing rail operators. At

present, all forecasts assume the same level of services operate on the existing rail and air

routes despite large reductions in the numbers of passengers. If air and rail services were

reduced to reflect reduced available revenue, this would in turn increase the market size for

HSR options.

Beyond the development of options, further refinement of the forecasting approach can be

undertaken to improve the robustness of forecasts and the quality of the data which was made

available for Phase 2 work. This includes highway count data, and improved data on existing

travel to and from Sweden by road and rail. This will also allow a much better representation of

potential demand on the Gothenburg and Stockholm corridors.

0%

10%

20%

30%

40%

50%

60%

Oslo - Bergen (Hallingdal)

Oslo - Kristiansand - Stavanger

Oslo - Trondheim Oslo - Stockholm





A. NSB Zone definitions (station groupings)

Table A.1 - NSB Zone Definitions

Zone Stations Boroughs, Counties

Trondheim Berkåk-Vikhammer Trondheim, Agdenes, Rennebu, Meldal, Orkdal, Midtre Gauldal, Melhus, Skaun, Klæbu

Stjørdal Hallstad-Åsen Malvik, Selbu, Tydal, Meråker, Stjørdal, Frosta

Levanger Ronglan-Verdal Leksvik, Levanger, Verdal, Mosvik

Steinkjer Røra-Grong Verran, Namdalseid, Inderøy, Snåsa

Mosjøen Majavatn-Bolna Steinkjer, Namsos, Alstahaug, Leirfjord, Vefsn, Grane, Hattfjelldal, Dønna, Nesna, Hemnes, Rana

Lillehammer Ringebu-Moelv Lillehammer, deler av Ringsaker, Nordre Land, Ringebu Øyer og Gausdal.

Hamar Brumunddal/Rena-Tangen Hamar, Stange, deler av Ringsaker, Løten, Elverum og Åmot

Lillestrøm Stasjoner på Romerike og Nittedal Alle kommuner på Romerike

Oslo S Stasjoner i Oslo og Oppegård Oslo kommune, Nesodden og Oppegård

Lysaker Lysaker - Slependen Bærum kommune

Asker Billingstad-Asker-Spikkestadlinjen Asker, Røyken og Hurum

Drammen Drammen-Sande/Darbu/Drolsum Drammen, Lier, Sande, Svelvik, Nedre Eiker, Øvre Eiker, Modum

Kongsberg Skollenborg, Kongsberg, Notodden - Trykkerud Kongsberg, Flesberg, Notodden

Tønsberg Holmestrand-Larvik Holmestrand, Hof, Horten, Re, Tønsberg, Nøtterøy, Tjøme, Sandefjord, Stokke, Larvik, Andebu og Lardal

Skien Porsgrunn, Skien – Hjuksebø/Neslandsvatn Porsgrunn, Skien, Siljan, Bamble, Kragerø, Drangedal, Nome, Bø, Sauherad

Ski Vevelstad-Ski-Vestby/Heia Ski, Vestby (ikke Son), Ås, Frogn, Rømskog, Trøgstad, Spydeberg, Askim, Eidsberg

Moss Sonsveien-Rygge Vestby (Son), Moss, Rygge, Hobøl, Skiptvet

Fredrikstad Råde-Halden/Rakkestad Råde, Fredrikstad, Halden, Sarpsborg, Hvaler, Aremark, Marker, Rakkestad

Stavanger Stavanger-Ganddal Stavanger, Randaberg, Sandnes, Sola

Bryne Øksnavadporten – Vigrestad. Hå, Klepp, Time, Gjesdal

Egersund Brusand-Sira Egersund, Sokndal, Lund, Bjerkreim

Mandal Audnedal Mandal, Farsund, Lindesnes og Lyngdal

Kristiansand Marnardal – Hynnekleiv Lillesand, Birkenes, Iveland, Kristiansand, Vennesla, Songdalen, Søgne, Marnardal

Arendal Gjerstad-Nelaug-Arendal Risør, Grimstad, Arendal, Gjerstad, Vegårshei, Froland, Tvedestrand

Bergen Bergen Bergen (- 3 bydeler), Os, Sund, Fjell, Askøy,

Arna Arna –Stanghelle Indre Arna, Ytre Arna, Espeland bydeler i Bergen, Meland, Radøy, Austrheim, Osterøy og Lindås.

Voss Dale – Vieren Ulvik, Granvin, Voss



B. Assumed enhancements in Do Minimum matrices

B.1 Do Minimum: road enhancements

The table below shows the highways projects which were considered by TØI in producing the NTM5 future year Do Minimum matrices. Most of these are drawn from the Norwegian National Transport Plan (NTP) 2010-2019.

NTP Corridor 2 Oslo – Ørje/Magnor NTP Corridor 6 (continued)

E18 Sydhavna E6 Sluppen - Stavne

Corridor 3 Oslo–Grenland–Kristiansand E6 Nidelv bru-Grilstad

E39 Tjensvollkrysset E6 Mjøen - Oppdal S

Bussterminal Oslo Rv 4 Lygna sør

E18 Vinterkjærkrysset Rv4 Fossumdiagonalen NY

E18 Ny Varoddbru - ny trprg Rv 3 Søndre Bjørå bru - Atna

NTP Corridor 4 Stavanger–Bergen–Ålesund Langevatnet - Ospeli bru

E39 Jektevik - Sandvikvåg E136 Flatmark - Monge

E39 Nyborgkrysset inkl. refusjon E136 Monge - Marstein

Lavik Fergekai Rv. 70 Freifjordtunnelen

Langeland - Moskog Utbedring Rv. 70 Opdølstranda

Lotetunnelen - Eid NTP Corridor 7 Trondheim–Bodø

Rv 13 Bugjelet - Brimnes inkl refusjon Storforshei-Bolna

NTP Corridor 5 Oslo–Bergen/Haugesund NTP Corridor 8 Bodø– Narvik–Tromsø–Kirkenes

Loftesnes bru [bridge] Narvik sentrum

NTP Corridor 6 Oslo–Trondheim Indre Nordnes - Skardalen

E6 Nordre avlastningsveg i Nidelv bru - Grilstad Tana bru

Nidelv bru refusjon Riksgrensen - Skibotn

Rv150 Ulvensplitten - Sinsen ny Skaidi - Hammerfest

Alnabruterminalen Hesseng - Riksgrense Russland

B.2 Do Minimum: Classic Rail enhancements

With regard to classic rail services, the following double-tracking projects are included in the NTP. The four schemes shown in italics are included in the NTM5 Do Minimum coding for the each of the future years, with timetables provided by Jernbaneverket. However, inspection of the NTM5 code revealed no effect on future long distance levels of service for classic rail within the HSR corridors. Double tracking:

Barkåker-Tønsberg Trønderbanen (including some extensions beyond NTP)

Gevingåsen Fjernstyring Mosjøen-Bodø

Lysaker-Sandvika Eidsvoll-Hamar (not in NTP 2010-2020)

Sandnes-Stavanger Sandbukta-Fredrikstad (not in NTP 2010-2020)

Oslo-Ski Drammen-Tønsberg; (not in NTP 2010-2020)

Holm-Holmestrand-Nykirke Fjernstyring Mosjøen-Bodø

Farriseidet-Porsgrunn

B.3 Do Minimum: Changes to levels of service on other modes (air, bus and ferry)

For all domestic aviation routes, the level of service is assumed to be unchanged from 2006. For long-distance buses, an increase in frequency of 25% has been included for bus services with a frequency less than once every hour. For boat travel, a 1% per annum increase in frequency is assumed for routes serving Oslo, Bergen and Stavanger. On other routes, 0.5% per year is applied.


C. Demand Tables (future year journeys by mode)


C.1 Oslo – Bergen

C.1.1 Oslo-Bergen (route Hallingdal) calling at Hønefoss, Gol and Voss 2024: Scenario C

Oslo-Bergen (Hallingdal) Hønefoss Gol Voss HSR Car Air Bus Classic

Rail Generated

Oslo/Akershus - Bergen

Scenario C 408,000 320,000 443,000 58,000 267,000

Mode Share 26% 22% 30% 4% 18%

Increment 408,000 -50,000 -180,000 -9,000 -45,000 124,000

Oslo/Akershus - intermediate areas

Scenario C 272,000 3,748,000 181,000 287,000 299,000

Mode Share 6% 78% 4% 6% 6%

Increment 272,000 -64,000 -89,000 -12,000 -15,000 92,000

Bergen - intermediate areas

Scenario C 65,000 845,000 50,000 79,000 67,000

Mode Share 6% 76% 5% 7% 6%

Increment 65,000 -13,000 -27,000 -1,000 -5,000 19,000

Oslo/Akershus - other HSR corridors

Scenario C 104,000 21,293,000 2,995,000 1,788,000 2,420,000

Mode Share 0% 79% 7% 7% 7%

Increment 104,000 -23,000 -44,000 -2,000 -3,000 32,000

Bergen - other HSR corridors

Scenario C 83,000 1,829,000 879,000 213,000 112,000

Mode Share 0% 75% 11% 6% 8%

Increment 83,000 -65,000 -37,000 -2,000 -3,000 -24,000

Other

Scenario C 182,000 2,600,009,000 9,186,000 2,475,000 40,202,000

Mode Share 0% 98% 0% 0% 2%

Increment 182,000 -3,000 -63,000 -10,000 -2,000 104,000

Total

Scenario C 1,114,000 2,628,044,000 13,734,000 4,900,000 43,367,000

Mode Share 0% 98% 1% 0% 2%

Increment 1,114,000 -218,000 -440,000 -36,000 -73,000 347,000

C.1.2 Oslo-Bergen (route Numedal) calling at Voss 2024 Scenario D

Oslo-Bergen (Numedal) Voss HSR Car Air Bus Classic

Rail Generated


Scenario D 620,000 300,000 359,000 54,000 247,000

Mode Share 38% 19% 23% 3% 16%

Increment 620,000 -70,000 -264,000 -13,000 -65,000 208,000


Scenario D 378,000 3,727,000 156,000 284,000 293,000

Mode Share 8% 77% 3% 6% 6%

Increment 378,000 -85,000 -114,000 -15,000 -21,000 143,000


Scenario D 75,000 845,000 45,000 78,000 66,000

Mode Share 7% 76% 4% 7% 6%

Increment 75,000 -13,000 -32,000 -2,000 -6,000 22,000


Scenario D 144,000 21,288,000 2,972,000 1,787,000 2,420,000

Mode Share 0% 79% 7% 7% 7%

Increment 144,000 -28,000 -67,000 -3,000 -3,000 43,000


Scenario D 111,000 1,828,000 863,000 213,000 110,000

Mode Share 0% 75% 11% 6% 8%

Increment 111,000 -86,000 -53,000 -2,000 -5,000 -35,000

Other

Scenario D 203,000 2,600,009,000 9,172,000 2,475,000 40,201,000

Mode Share 0% 98% 0% 0% 2%

Increment 203,000 17,000 -77,000 -10,000 -3,000 130,000

Total

Scenario D 1,531,000 2,627,997,000 13,567,000 4,891,000 43,337,000

Mode Share 0% 98% 1% 0% 2%

Increment 1,531,000 -265,000 -607,000 -45,000 -103,000 511,000


C.1.3 Oslo-Bergen/Stavanger (route Haukeli) non-stop 2024: Scenario D

Oslo-Bergen (Haukeli) non-stop HSR Car Air Bus Classic

Rail Generated


Scenario D 686,000 295,000 338,000 53,000 239,000

Mode Share 41% 19% 22% 3% 15%

Increment 686,000 -75,000 -285,000 -14,000 -73,000 239,000


Scenario D 270,000 3,757,000 174,000 290,000 297,000

Mode Share 6% 79% 4% 6% 6%

Increment 270,000 -55,000 -96,000 -9,000 -17,000 93,000


Scenario D 67,000 847,000 50,000 79,000 66,000

Mode Share 6% 76% 5% 7% 6%

Increment 67,000 -11,000 -27,000 -1,000 -6,000 22,000


Scenario D 1,017,000 21,159,000 2,592,000 1,769,000 2,378,000

Mode Share 0% 79% 7% 7% 7%

Increment 1,017,000 -157,000 -447,000 -21,000 -45,000 347,000


Scenario D 136,000 1,822,000 851,000 212,000 110,000

Mode Share 0% 75% 11% 6% 8%

Increment 136,000 -97,000 -65,000 -3,000 -5,000 -34,000

Other

Scenario D 319,000 2,599,992,000 9,114,000 2,474,000 40,195,000

Mode Share 0% 98% 0% 0% 2%

Increment 319,000 5,000 -135,000 -11,000 -9,000 169,000

Total

Scenario D 2,495,000 2,627,872,000 13,119,000 4,877,000 43,285,000

Mode Share 0% 98% 0% 0% 2%

Increment 2,495,000 -390,000 -1,055,000 -59,000 -155,000 836,000

Oslo-Stavanger (Haukeli) non-stop HSR Car Air Bus Classic

Rail Generated

Oslo/Akershus - Stavanger

Scenario D 467,000 195,000 254,000 27,000 71,000

Mode Share 46% 19% 25% 3% 7%

Increment 467,000 -56,000 -217,000 -7,000 -24,000 163,000


Scenario D 355,000 10,276,000 322,000 915,000 1,138,000

Mode Share 3% 79% 2% 7% 9%

Increment 355,000 -61,000 -147,000 -8,000 -21,000 118,000

Stavanger - intermediate areas

Scenario D 72,000 799,000 124,000 56,000 106,000

Mode Share 6% 69% 11% 5% 9%

Increment 72,000 -12,000 -34,000 -1,000 -3,000 22,000


Scenario D 1,151,000 14,739,000 2,528,000 1,170,000 1,704,000

Mode Share 0% 71% 14% 5% 10%

Increment 1,151,000 -171,000 -464,000 -29,000 -91,000 396,000

Stavanger - other HSR corridors

Scenario D 67,000 1,259,000 433,000 120,000 104,000

Mode Share 0% 71% 14% 6% 9%

Increment 67,000 -70,000 -31,000 -2,000 -1,000 -37,000

Other

Scenario D 383,000 2,600,604,000 9,458,000 2,589,000 40,162,000

Mode Share 0% 98% 0% 0% 2%

Increment 383,000 -20,000 -162,000 -12,000 -15,000 174,000

Total

Scenario D 2,495,000 2,627,872,000 13,119,000 4,877,000 43,285,000

Mode Share 0% 98% 0% 0% 2%

Increment 2,495,000 -390,000 -1,055,000 -59,000 -155,000 836,000


C.2 Stavanger – Bergen

C.2.1 Stavanger-Bergen (route Haugesund) calling at Haugesund 2024: Scenario D

Stavanger-Bergen (Haugesund) Haugesund HSR Car Air Bus Classic

Rail Generated

Stavanger-Bergen

Scenario D 231,000 310,000 87,000 40,000 4,000

Mode Share 34% 46% 13% 6% 1%

Increment 231,000 -41,000 -85,000 -6,000 0 99,000

Stavanger-Corridor

Scenario D 1,000 222,000 2,000 15,000 0

Mode Share 0% 92% 1% 6% 0%

Increment 1,000 0 -1,000 0 0 0

Bergen-Corridor

Scenario D 137,000 470,000 37,000 43,000 0

Mode Share 20% 68% 5% 6% 0%

Increment 137,000 -44,000 -30,000 -4,000 0 59,000

Stavanger-Other corridors

Scenario D 79,000 1,742,000 891,000 150,000 304,000

Mode Share 0% 82% 11% 7% 0%

Increment 79,000 -20,000 -27,000 -2,000 -1,000 29,000

Bergen-Other corridors

Scenario D 176,000 2,172,000 1,302,000 266,000 493,000

Mode Share 0% 56% 29% 5% 10%

Increment 176,000 -76,000 -70,000 -3,000 -2,000 25,000

Other

Scenario D 111,000 2,623,172,000 10,217,000 4,403,000 42,637,000

Mode Share 0% 98% 0% 0% 2%

Increment 111,000 7,000 -34,000 -4,000 1,000 81,000

Total

Scenario D 735,000 2,628,088,000 12,536,000 4,917,000 43,438,000

Mode Share 0% 98% 0% 0% 2%

Increment 735,000 -174,000 -247,000 -19,000 -2,000 293,000


C.3 Oslo – Stavanger

C.3.1 Oslo-Stavanger (route Kristiansand) calling at all stations 2024: Scenario C

Oslo-Stavanger (Kristiansand) All stations HSR Car Air Bus Classic

Rail Generated

Oslo/Akershus - Stavanger

Scenario C 216,000 220,000 368,000 30,000 83,000

Mode Share 24% 24% 40% 3% 9%

Increment 216,000 -31,000 -103,000 -4,000 -12,000 66,000


Scenario C 371,000 10,235,000 355,000 907,000 1,139,000

Mode Share 3% 79% 3% 7% 9%

Increment 371,000 -102,000 -114,000 -16,000 -20,000 119,000

Stavanger - intermediate areas

Scenario C 144,000 776,000 106,000 54,000 100,000

Mode Share 12% 66% 9% 5% 8%

Increment 144,000 -35,000 -52,000 -3,000 -9,000 45,000


Scenario C 214,000 14,868,000 2,907,000 1,188,000 1,782,000

Mode Share 0% 71% 14% 5% 10%

Increment 214,000 -42,000 -85,000 -11,000 -13,000 63,000

Stavanger - other HSR corridors

Scenario C 114,000 1,249,000 431,000 119,000 90,000

Mode Share 0% 71% 14% 6% 9%

Increment 114,000 -55,000 -33,000 -3,000 -15,000 8,000

Other

Scenario C 263,000 2,600,616,000 9,524,000 2,593,000 40,161,000

Mode Share 0% 98% 0% 0% 2%

Increment 263,000 -33,000 -96,000 -8,000 -16,000 110,000

Total

Scenario C 1,322,000 2,627,964,000 13,691,000 4,891,000 43,355,000

Mode Share 0% 98% 1% 0% 2%

Increment 1,322,000 -298,000 -483,000 -45,000 -85,000 411,000


C.3.2 Oslo-Stavanger (route Kristiansand) calling at Porsgrunn and Kristiansand 2024: Scenario D

Oslo-Stavanger (Kristiansand) Porsgrunn HSR Car Air Bus Classic

Rail Generated

Oslo-Stavanger

Scenario D 414,000 200,000 274,000 27,000 74,000

Mode Share 42% 20% 28% 3% 7%

Increment 414,000 -51,000 -197,000 -7,000 -21,000 138,000

Oslo-Corridor

Scenario D 497,000 10,231,000 291,000 905,000 1,130,000

Mode Share 4% 78% 2% 7% 9%

Increment 497,000 -106,000 -178,000 -18,000 -29,000 166,000

Stavanger-Corridor

Scenario D 196,000 770,000 79,000 54,000 100,000

Mode Share 16% 64% 7% 4% 8%

Increment 196,000 -41,000 -79,000 -3,000 -9,000 64,000

Oslo-Other corridors

Scenario D 401,000 14,839,000 2,837,000 1,180,000 1,772,000

Mode Share 0% 71% 14% 5% 10%

Increment 401,000 -71,000 -155,000 -19,000 -23,000 133,000

Stavanger-Other corridors

Scenario D 95,000 1,255,000 414,000 120,000 100,000

Mode Share 0% 71% 14% 6% 9%

Increment 95,000 -69,000 -50,000 -2,000 -5,000 -31,000

Other

Scenario D 354,000 2,600,601,000 9,473,000 2,591,000 40,164,000

Mode Share 0% 98% 0% 0% 2%

Increment 354,000 -28,000 -147,000 -10,000 -13,000 156,000

Total

Scenario D 1,957,000 2,627,896,000 13,368,000 4,877,000 43,340,000

Mode Share 0% 98% 0% 0% 2%

1,957,000 -366,000 -806,000 -59,000 -100,000 626,000


C.4 Oslo – Trondheim

C.4.1 Oslo-Trondheim (route Hamar) calling at all stations 2024: Scenario C

Oslo-Trondheim (Hamar) All stations HSR Car Air Bus Classic

Rail Generated

Oslo/Akershus - Trondheim

Scenario C 453,000 347,000 347,000 54,000 154,000

Mode Share 33% 26% 26% 4% 11%

Increment 453,000 -67,000 -197,000 -10,000 -33,000 146,000


Scenario C 179,000 7,538,000 310,000 586,000 733,000

Mode Share 2% 81% 3% 6% 8%

Increment 179,000 -44,000 -65,000 -5,000 -11,000 54,000

Trondheim - intermediate areas

Scenario C 74,000 1,585,000 33,000 103,000 87,000

Mode Share 4% 84% 2% 5% 5%

Increment 74,000 -51,000 -17,000 -3,000 -5,000 -2,000


Scenario C 30,000 17,496,000 3,000,000 1,500,000 2,117,000

Mode Share 0% 87% 3% 6% 5%

Increment 30,000 -6,000 -13,000 -1,000 -1,000 9,000

Trondheim - other HSR corridors

Scenario C 402,000 523,000 804,000 59,000 54,000

Mode Share 0% 73% 12% 6% 9%

Increment 402,000 -89,000 -341,000 -2,000 -2,000 -32,000

Other

Scenario C 338,000 2,600,568,000 8,808,000 2,606,000 40,240,000

Mode Share 0% 98% 0% 0% 2%

Increment 338,000 52,000 -239,000 -7,000 -3,000 141,000

Total

Scenario C 1,476,000 2,628,057,000 13,302,000 4,908,000 43,385,000

Mode Share 0% 98% 0% 0% 2%

Increment 1,476,000 -205,000 -872,000 -28,000 -55,000 316,000

C.4.2 Oslo-Trondheim (route Hamar) calling at Gardermoen 2024: Scenario D

Oslo-Stavanger (Hamar) Gardermoen HSR Car Air Bus Classic

Rail Generated

Oslo-Trondheim

Scenario D 627,000 327,000 284,000 51,000 142,000

Mode Share 44% 23% 20% 4% 10%

Increment 627,000 -87,000 -260,000 -13,000 -45,000 222,000

Oslo-Corridor

Scenario D 239,000 7,530,000 284,000 585,000 730,000

Mode Share 3% 80% 3% 6% 8%

Increment 239,000 -52,000 -91,000 -6,000 -14,000 76,000

Trondheim-Corridor

Scenario D 34,000 1,600,000 36,000 105,000 90,000

Mode Share 2% 86% 2% 6% 5%

Increment 34,000 -36,000 -14,000 -1,000 -2,000 -19,000


Scenario D 4,000 17,501,000 3,011,000 1,502,000 2,118,000

Mode Share 0% 87% 3% 6% 5%

Increment 4,000 -1,000 -2,000 1,000 0 2,000

Trondheim-Other corridors

Scenario D 543,000 517,000 686,000 59,000 53,000

Mode Share 0% 73% 12% 6% 9%

Increment 543,000 -115,000 -459,000 -2,000 -3,000 -36,000

Other

Scenario D 350,000 2,600,586,000 8,759,000 2,607,000 40,242,000

Mode Share 0% 98% 0% 0% 2%

Increment 350,000 90,000 -288,000 -6,000 -1,000 145,000

Total

Scenario D 1,797,000 2,628,061,000 13,060,000 4,909,000 43,375,000

Mode Share 0% 98% 0% 0% 2%

Increment 1,797,000 -201,000 -1,114,000 -27,000 -65,000 390,000


C.5 Oslo – Stockholm

C.5.1 Oslo-Stockholm (route Karlstad) calling at all stations 2024: Scenario C

Oslo-Stockholm (Karlstad) All stations HSR Car Air Bus Classic

Rail Generated

Oslo-Stockholm

Scenario D 689,000 314,000 465,000 0 20,000

Mode Share 46% 21% 31% 0% 1%

Increment 689,000 -46,000 -366,000 0 -5,000 272,000

Oslo-Corridor

Scenario D 0 532,000 0 47,000 0

Mode Share 0% 92% 0% 8% 0%

Increment 0 0 0 0 0 0

Stockholm-Corridor

Scenario D 2,000 4,000 1,000 0 0

Mode Share 26% 60% 14% 0% 0%

Increment 2,000 0 0 0 0 2,000


Scenario D 30,000 24,598,000 3,090,000 2,108,000 3,022,000

Mode Share 0% 80% 20% 0% 0%

Increment 30,000 -8,000 -11,000 -1,000 -2,000 8,000

Stockholm-Other corridors

Scenario D 9,000 2,777,888,000 1,670,000 0 53,394,000

Mode Share 0% 75% 9% 6% 9%

Increment 9,000 -51,000 -3,000 0 0 -45,000

Other

Scenario D 8,000 -175,134,000 8,565,000 2,779,000 -

13,003,000

Mode Share 0% 99% -5% -2% 7%

Increment 8,000 45,000 -3,000 -1,000 0 49,000

Total

Scenario D 738,000 2,628,202,000 13,791,000 4,934,000 43,433,000

Mode Share 0% 98% 1% 0% 2%

Increment 738,000 -60,000 -383,000 -2,000 -7,000 286,000

C.5.2 Oslo-Stockholm (route Karlstad) calling at Lillestrøm 2024: Scenario D

Oslo-Stockholm (Karlstad) Lillestrøm HSR Car Air Bus Classic

Rail Generated

Oslo-Stockholm

Scenario D 779,000 308,000 428,000 0 20,000

Mode Share 51% 20% 28% 0% 1%

Increment 779,000 -52,000 -403,000 0 -5,000 319,000

Oslo-Corridor

Scenario D 0 532,000 0 47,000 0

Mode Share 0% 92% 0% 8% 0%


Stockholm-Corridor

Scenario D 1,000 4,000 1,000 0 0

Mode Share 17% 67% 16% 0% 0%

Increment 1,000 0 0 0 0 1,000


Scenario D 25,000 24,600,000 3,091,000 2,108,000 3,022,000

Mode Share 0% 80% 20% 0% 0%

Increment 25,000 -6,000 -10,000 -1,000 -2,000 6,000


Scenario D 10,000 2,777,888,000 1,669,000 0 53,394,000

Mode Share 0% 75% 9% 6% 9%

Increment 10,000 -57,000 -4,000 0 0 -51,000

Other

Scenario D 7,000 -175,134,000 8,567,000 2,779,000 -

13,003,000

Mode Share 0% 99% -5% -2% 7%

Increment 7,000 51,000 -1,000 -1,000 0 56,000

Total

Scenario D 822,000 2,628,198,000 13,756,000 4,934,000 43,433,000

Mode Share 0% 98% 1% 0% 2%

Increment 822,000 -64,000 -418,000 -2,000 -7,000 331,000


C.6 Oslo – Gothenburg

C.6.1 Oslo-Gothenburg (route Halden) non-stop 2024: Scenario D

Oslo-Gothenburg (Halden) non-Stop HSR Car Air Bus Classic

Rail Generated

Oslo-Stockholm

Scenario D 827,000 1,134,000 0 0 6,000

Mode Share 42% 58% 0% 0% 0%

Increment 827,000 -554,000 -12,000 0 -1,000 260,000

Oslo-Corridor

Scenario D 0 1,863,000 0 220,000 315,000

Mode Share 0% 78% 0% 9% 13%


Stockholm-Corridor

Scenario D 0 11,000 1,000 0 10,000

Mode Share 1% 50% 3% 0% 45%



Scenario D 0 20,817,000 3,912,000 1,936,000 2,722,000

Mode Share 0% 50% 5% 0% 45%



Scenario D 0 1,300,000 5,000 0 9,000

Mode Share 0% 71% 13% 7% 9%

Increment 0 -554,000 0 0 0 -554,000

Other

Scenario D 1,000 32,242,000 8,687,000 2,780,000 1,674,000

Mode Share 0% 71% 19% 6% 4%

Increment 1,000 554,000 0 0 0 555,000

Total

Scenario D 828,000 57,367,000 12,605,000 4,936,000 4,736,000

Mode Share 1% 71% 16% 6% 6%

Increment 828,000 -554,000 -12,000 0 -1,000 261,000


C.7 County-to-county Matrices

C.7.1 HSR journeys (over 100 km) county-to-county matrix: Oslo-Bergen (Hallingdal) calling at Hønefoss, Gol and Voss: Scenario C 2024

County to/from

Østfold

Akers

hus

Oslo

Hedm

ark

Oppla

nd

Buskeru

d

Vestf

old

Te

lem

ark

Aust-

Agder

Vest-

Agder

Rogala

nd

Hord

ala

nd

Sogn o

g F

jord

ane

Mø

re o

g R

om

sdal

Sø

r-T

røn

dela

g

Nord

-Trø

ndela

g

Nord

land

Tro

ms R

om

sa

Fin

nm

ark

Fin

nm

àrk

u

Østfold 0 0 0 139 22 18 0 0 5 1 1265 17457 1938 63 290 16 0 0 0

Akershus 0 0 0 455 193 167 0 2 115 22 5841 72213 9685 1208 1058 60 0 0 0

Oslo 0 0 0 2475 548 686 0 10 624 104 19270 234941 32135 4655 4374 279 1 0 0

Hedmark 142 461 2509 47 53 315 60 6 51 41 587 7872 1149 99 77 5 0 0 0

Oppland 23 193 548 53 0 27 10 1 190 153 1832 17457 2494 292 125 7 0 0 0

Buskerud 18 167 686 310 26 0 0 0 182 158 3444 37427 4594 320 639 36 0 0 0

Vestfold 0 0 0 59 10 0 0 0 0 0 788 15229 1264 6 219 14 0 0 0

Telemark 0 2 9 6 1 0 0 0 0 0 172 3556 282 1 39 2 0 0 0

Aust-Agder 5 112 614 51 190 182 0 0 0 0 64 2071 46 0 0 0 0 0 0

Vest-Agder 1 21 101 41 153 159 0 0 0 0 5 283 103 0 0 0 0 0 0

Rogaland 1286 5825 19223 586 1829 3469 806 178 64 5 0 7082 4293 14 1 0 0 0 0

Hordaland 17399 75542 252451 8110 18130 37599 15068 3514 2123 295 7077 525 11794 4246 970 60 0 0 0

Sogn og Fjordane 1934 9922 32860 1181 2566 4626 1254 279 48 106 4292 11701 0 41 189 11 0 0 0

Møre og Romsdal 65 1280 4801 102 303 331 6 1 0 0 14 4244 40 0 6 0 0 0 0

Sør-Trøndelag 296 1085 4448 78 129 659 223 40 0 0 1 970 189 6 0 0 0 0 0

Nord-Trøndelag 16 59 273 5 7 36 14 2 0 0 0 60 11 0 0 0 0 0 0

Nordland 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Troms Romsa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Finnmark Finnmàrku 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0


C.7.2 HSR journeys (over 100 km) county-to-county matrix: Oslo-Bergen (Numedal) calling at Voss only: Scenario D 2024

County to/from

Østfold

Akers

hus

Oslo

Hedm

ark

Oppla

nd

Buskeru

d

Vestf

old

Te

lem

ark

Aust-

Agder

Vest-

Agder

Rogala

nd

Hord

ala

nd

Sogn o

g F

jord

ane

Mø

re o

g R

om

sdal

Sø

r-T

røn

dela

g

Nord

-Trø

ndela

g

Nord

land

Tro

ms R

om

sa

Fin

nm

ark

Fin

nm

àrk

u

Østfold 0 0 0 0 2 1 0 0 10 2 2345 26435 2599 86 28 0 0 0 0

Akershus 0 0 0 0 19 15 0 0 202 42 10774 108433 12974 1537 104 0 0 0 0

Oslo 0 0 0 0 52 53 0 0 1135 211 35156 352784 42086 6118 408 0 0 0 0

Hedmark 0 0 0 0 1 1 0 0 15 2 784 9164 1188 97 5 0 0 0 0

Oppland 2 18 49 1 0 2 1 0 15 9 1079 11197 916 71 5 0 0 0 0

Buskerud 1 14 51 1 2 0 0 0 17 8 4495 43556 4339 112 50 0 0 0 0

Vestfold 0 0 0 0 1 0 0 0 0 0 1488 26165 1783 8 21 0 0 0 0

Telemark 0 0 0 0 0 0 0 0 0 0 300 6008 397 1 4 0 0 0 0

Aust-Agder 9 198 1120 15 15 17 0 0 0 0 78 2524 83 0 0 0 0 0 0

Vest-Agder 2 41 207 2 9 8 0 0 0 0 9 506 149 0 0 0 0 0 0

Rogaland 2388 10746 35071 782 1076 4547 1526 312 78 9 0 7896 4674 16 1 0 0 0 0

Hordaland 26347 112602 374334 9440 11722 43649 25923 5942 2588 529 7891 663 13083 4946 496 12 0 0 0

Sogn og Fjordane 2594 13265 42969 1221 944 4373 1774 393 85 154 4674 12985 0 0 10 2 0 0 0

Møre og Romsdal 89 1663 6382 100 73 116 8 1 0 0 16 4946 0 0 0 0 0 0 0

Sør-Trøndelag 28 107 414 5 5 51 21 4 0 0 1 496 10 0 0 0 0 0 0

Nord-Trøndelag 0 0 0 0 0 0 0 0 0 0 0 12 2 0 0 0 0 0 0

Nordland 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Troms Romsa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0



C.7.3 HSR journeys (over 100 km) county-to-county matrix: Stavanger-Bergen (Haugesund) calling at Haugesund: Scenario D 2024

County to/from

Østfold

Akers

hus

Oslo

Hedm

ark

Oppla

nd

Buskeru

d

Vestf

old

Te

lem

ark

Aust-

Agder

Vest-

Agder

Rogala

nd

Hord

ala

nd

Sogn o

g F

jord

ane

Mø

re o

g R

om

sdal

Sø

r-T

røn

dela

g

Nord

-Trø

ndela

g

Nord

land

Tro

ms R

om

sa

Fin

nm

ark

Fin

nm

àrk

u

Østfold 0 0 0 0 0 0 0 0 0 0 164 266 6 0 0 0 0 0 0

Akershus 0 0 0 0 0 0 0 0 1 2 546 509 15 2 0 0 0 0 0

Oslo 0 0 0 0 0 0 0 0 2 3 1467 1561 54 6 0 0 0 0 0

Hedmark 0 0 0 0 0 0 0 0 1 1 159 12 0 0 0 0 0 0 0

Oppland 0 0 0 0 0 0 0 0 7 14 1123 96 0 0 0 0 0 0 0

Buskerud 0 0 0 0 0 0 0 0 7 12 1429 673 17 0 0 0 0 0 0

Vestfold 0 0 0 0 0 0 0 0 0 0 354 690 13 0 0 0 0 0 0

Telemark 0 0 0 0 0 0 0 0 0 0 697 1680 27 0 0 0 0 0 0

Aust-Agder 0 1 2 1 7 7 0 0 0 0 51 4384 134 0 0 0 0 0 0

Vest-Agder 0 2 4 1 14 12 0 0 0 0 151 7710 259 1 0 0 0 0 0

Rogaland 160 541 1447 160 1121 1432 345 686 50 149 0 332531 7125 54 3 0 0 0 0

Hordaland 265 543 1719 11 93 672 690 1662 4485 8056 332036 5844 511 3 0 0 0 0 0

Sogn og Fjordane 6 16 57 0 0 17 13 26 138 267 7125 518 0 0 0 0 0 0 0

Møre og Romsdal 0 2 6 0 0 0 0 0 0 1 54 3 0 0 0 0 0 0 0

Sør-Trøndelag 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0

Nord-Trøndelag 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Nordland 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Troms Romsa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0



C.7.4 HSR journeys (over 100 km) county-to-county matrix: Oslo-Stavanger (Kristiansand) calling at all stations: Scenario C 2024

County to/from

Østfold

Akers

hus

Oslo

Hedm

ark

Oppla

nd

Buskeru

d

Vestf

old

Te

lem

ark

Aust-

Agder

Vest-

Agder

Rogala

nd

Hord

ala

nd

Sogn o

g F

jord

ane

Mø

re o

g R

om

sdal

Sø

r-T

røn

dela

g

Nord

-Trø

ndela

g

Nord

land

Tro

ms R

om

sa

Fin

nm

ark

Fin

nm

àrk

u

Østfold 0 0 0 29 1 6 0 0 708 1048 14756 993 25 7 25 2 0 0 0

Akershus 0 0 0 41 4 63 249 68 15314 20563 55840 3452 107 133 47 3 0 0 0

Oslo 0 0 0 0 0 237 0 15 60545 64708 166893 11430 392 545 0 0 0 0 0

Hedmark 30 43 0 0 0 312 139 21 1209 1526 4262 206 6 8 0 0 0 0 0

Oppland 1 4 0 0 0 8 6 1 1145 1409 3335 164 5 6 0 0 0 0 0

Buskerud 6 63 237 305 8 0 0 0 1998 2758 29986 1897 56 15 300 23 0 0 0

Vestfold 0 249 0 138 6 0 0 0 120 863 28517 1829 37 2 172 15 0 0 0

Telemark 0 68 15 21 1 0 0 0 0 19 18629 1296 23 1 62 5 0 0 0

Aust-Agder 707 15314 60545 1209 1145 1998 120 0 0 0 26876 2623 88 1 1 0 0 0 0

Vest-Agder 1048 20563 64708 1526 1409 2758 863 19 0 0 99445 9142 389 1 1 0 0 0 0

Rogaland 15293 55712 166525 4251 3326 30388 29232 19354 26876 99319 0 0 0 2 2 0 0 0 0

Hordaland 990 3613 12252 211 173 1889 1811 1282 2706 9553 0 0 0 2 2 0 0 0 0

Sogn og Fjordane 25 111 407 6 5 56 36 22 91 400 0 0 0 0 0 0 0 0 0

Møre og Romsdal 8 147 570 8 7 15 2 1 1 1 2 2 0 0 0 0 0 0 0

Sør-Trøndelag 26 50 0 0 0 309 175 63 1 1 2 2 0 0 0 0 0 0 0

Nord-Trøndelag 2 4 0 0 0 24 15 5 0 0 0 0 0 0 0 0 0 0 0

Nordland 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Troms Romsa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0



C.7.5 HSR journeys (over 100 km) county-to-county matrix: Oslo-Stavanger (Kristiansand) calling at Kristiansand and Porsgrunn: Scenario D 2024

County to/from

Østfold

Akers

hus

Oslo

Hedm

ark

Oppla

nd

Buskeru

d

Vestf

old

Te

lem

ark

Aust-

Agder

Vest-

Agder

Rogala

nd

Hord

ala

nd

Sogn o

g F

jord

ane

Mø

re o

g R

om

sdal

Sø

r-T

røn

dela

g

Nord

-Trø

ndela

g

Nord

land

Tro

ms R

om

sa

Fin

nm

ark

Fin

nm

àrk

u

Østfold 0 0 0 16 1 0 0 0 434 1521 26928 2223 61 0 14 1 0 0 0

Akershus 0 0 0 0 0 0 400 87 8529 34541 105781 7812 255 0 0 0 0 0 0

Oslo 0 0 0 0 0 0 0 18 40123 110304 319591 26597 985 0 0 0 0 0 0

Hedmark 17 0 0 0 0 0 144 27 695 2474 9417 502 15 0 0 0 0 0 0

Oppland 1 0 0 0 0 0 6 2 651 2307 7706 411 12 0 0 0 0 0 0

Buskerud 0 0 0 0 0 0 0 0 830 3171 38772 2885 88 0 0 0 0 0 0

Vestfold 0 396 0 142 6 0 0 0 63 1705 53610 4289 87 2 138 12 0 0 0

Telemark 0 86 18 27 2 0 0 0 0 26 31100 2752 48 1 80 7 0 0 0

Aust-Agder 434 8529 40123 695 651 830 62 0 0 0 37554 4167 147 0 0 0 0 0 0

Vest-Agder 1521 34541 110304 2474 2307 3171 1705 26 0 0 69513 13524 575 2 2 0 0 0 0

Rogaland 27710 105589 319042 9395 7687 39210 54608 32027 37501 69351 0 0 0 3 3 0 0 0 0

Hordaland 2216 8242 28806 517 439 2877 4244 2721 4299 14092 0 0 0 3 5 0 0 0 0

Sogn og Fjordane 61 266 1028 15 13 88 86 47 151 591 0 0 0 0 0 0 0 0 0

Møre og Romsdal 0 0 0 0 0 0 2 1 0 2 3 3 0 0 0 0 0 0 0

Sør-Trøndelag 14 0 0 0 0 0 143 82 0 2 3 5 0 0 0 0 0 0 0

Nord-Trøndelag 1 0 0 0 0 0 12 7 0 0 0 0 0 0 0 0 0 0 0

Nordland 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Troms Romsa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0



C.7.6 HSR journeys (over 100 km) county-to-county matrix: Oslo-Trondheim (Hamar) calling at all stations: Scenario C 2024

County to/from

Østfold

Akers

hus

Oslo

Hedm

ark

Oppla

nd

Buskeru

d

Vestf

old

Te

lem

ark

Aust-

Agder

Vest-

Agder

Rogala

nd

Hord

ala

nd

Sogn o

g F

jord

ane

Mø

re o

g R

om

sdal

Sø

r-T

røn

dela

g

Nord

-Trø

ndela

g

Nord

land

Tro

ms R

om

sa

Fin

nm

ark

Fin

nm

àrk

u

Østfold 0 0 0 377 37 3 0 0 0 0 0 0 0 0 377 37 3 0 0

Akershus 0 0 0 1452 356 29 126 18 359 225 578 0 0 0 1452 356 29 126 18

Oslo 0 0 0 6384 875 91 0 0 0 0 0 0 0 0 6384 875 91 0 0

Hedmark 381 1469 6458 371 183 696 206 22 362 258 602 381 1469 6458 371 183 696 206 22

Oppland 37 352 875 178 0 42 15 1 269 215 411 37 352 875 178 0 42 15 1

Buskerud 2 29 88 683 41 0 0 0 9 6 9 2 29 88 683 41 0 0 0

Vestfold 0 128 0 205 15 0 0 0 0 0 0 0 128 0 205 15 0 0 0

Telemark 0 19 0 22 1 0 0 0 0 0 0 0 19 0 22 1 0 0 0

Aust-Agder 0 365 0 364 269 9 0 0 0 0 0 0 365 0 364 269 9 0 0

Vest-Agder 0 229 0 259 215 6 0 0 0 0 0 0 229 0 259 215 6 0 0

Rogaland 0 599 0 609 409 10 0 0 0 0 0 0 599 0 609 409 10 0 0

Hordaland 286 1476 4483 686 513 432 207 37 6 3 4 286 1476 4483 686 513 432 207 37

Sogn og Fjordane 376 2468 8500 961 678 685 186 31 8 5 4 376 2468 8500 961 678 685 186 31

Møre og Romsdal 276 5883 19055 2383 2185 481 28 3 1 1 1 276 5883 19055 2383 2185 481 28 3

Sør-Trøndelag 15132 64360 212377 18717 29146 26282 13398 2640 7 7 9 15132 64360 212377 18717 29146 26282 13398 2640

Nord-Trøndelag 1526 6207 25249 2223 3557 2902 1395 233 0 0 0 1526 6207 25249 2223 3557 2902 1395 233

Nordland 1 14 51 5 11 1 0 0 0 0 0 1 14 51 5 11 1 0 0

Troms Romsa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0



C.7.7 HSR journeys (over 100 km) county-to-county matrix: Oslo-Trondheim (Hamar) calling at Gardermoen only: Scenario D 2024

County to/from

Østfold

Akers

hus

Oslo

Hedm

ark

Oppla

nd

Buskeru

d

Vestf

old

Te

lem

ark

Aust-

Agder

Vest-

Agder

Rogala

nd

Hord

ala

nd

Sogn o

g F

jord

ane

Mø

re o

g R

om

sdal

Sø

r-T

røn

dela

g

Nord

-Trø

ndela

g

Nord

land

Tro

ms R

om

sa

Fin

nm

ark

Fin

nm

àrk

u

Østfold 0 0 0 53 7 0 0 0 0 0 0 0 2 161 21181 2452 1 0 0

Akershus 0 0 0 190 50 20 129 19 366 230 589 549 240 3648 89340 9788 22 0 0

Oslo 0 0 0 941 186 0 0 0 0 0 0 0 179 11866 291571 39505 79 0 0

Hedmark 53 190 956 30 17 104 70 9 251 167 390 313 114 488 13473 1540 3 0 0

Oppland 7 51 187 17 0 9 5 1 197 127 273 232 86 393 11015 1250 3 0 0

Buskerud 0 21 0 103 8 0 0 0 0 0 0 0 3 241 35171 4466 1 0 0

Vestfold 0 130 0 70 5 0 0 0 0 0 0 0 0 18 20301 2357 0 0 0

Telemark 0 19 0 9 1 0 0 0 0 0 0 0 0 2 4334 413 0 0 0

Aust-Agder 0 373 0 252 197 0 0 0 0 0 0 0 0 0 12 0 0 0 0

Vest-Agder 0 234 0 168 127 0 0 0 0 0 0 0 0 0 12 0 0 0 0

Rogaland 0 611 0 395 272 0 0 0 0 0 0 0 0 1 16 0 0 0 0

Hordaland 0 596 0 331 249 0 0 0 0 0 0 0 0 14 523 50 0 0 0

Sogn og Fjordane 2 254 180 120 90 3 0 0 0 0 0 0 0 4 196 16 0 0 0

Møre og Romsdal 166 3693 11980 492 399 242 18 2 0 0 1 14 4 0 0 0 0 0 0

Sør-Trøndelag 21439 90742 294137 13617 11217 35441 20505 4387 12 12 16 523 196 0 0 0 0 0 0

Nord-Trøndelag 2432 9710 38916 1562 1276 4421 2323 408 0 0 0 48 16 0 0 0 0 0 0

Nordland 1 20 74 3 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0

Troms Romsa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0



C.7.8 HSR journeys (over 100 km) county-to-county matrix: Oslo-Stockholm (Karlstad) calling at Lillestrøm and Kongsvinger: Scenario C 2024

County to/from

Østfold

Akers

hus

Oslo

Hedm

ark

Oppla

nd

Buskeru

d

Vestf

old

Te

lem

ark

Aust-

Agder

Vest-

Agder

Rogala

nd

Hord

ala

nd

Sogn o

g F

jord

ane

Mø

re o

g R

om

sdal

Sø

r-T

røn

dela

g

Nord

-Trø

ndela

g

Nord

land

Tro

ms R

om

sa

Fin

nm

ark

Fin

nm

àrk

u

Østfold 0 0 0 214 1 1 0 0 97 77 178 156 55 19 202 21 0 0 0

Akershus 0 0 0 755 36 51 140 21 1013 671 1523 1515 581 185 784 82 0 0 0

Oslo 0 0 0 3742 5 6 0 0 161 99 236 246 88 33 3012 355 1 0 0

Hedmark 218 764 3789 0 39 401 121 11 256 178 424 354 128 43 0 0 0 0 0

Oppland 1 37 5 38 0 0 1 0 45 31 71 54 21 7 36 4 0 0 0

Buskerud 1 52 7 396 0 0 0 0 0 0 0 0 0 0 369 39 0 0 0

Vestfold 0 142 0 121 1 0 0 0 0 0 0 0 0 0 148 18 0 0 0

Telemark 0 22 0 11 0 0 0 0 0 0 0 0 0 0 24 3 0 0 0

Aust-Agder 97 1021 165 258 45 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Vest-Agder 77 676 101 179 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Rogaland 178 1544 246 432 70 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Hordaland 162 1617 272 376 57 0 0 0 0 0 0 0 0 0 3 0 0 0 0

Sogn og Fjordane 57 612 94 135 22 0 0 0 0 0 0 0 0 0 1 0 0 0 0

Møre og Romsdal 19 196 35 45 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Sør-Trøndelag 205 800 3035 0 37 372 149 24 0 0 0 3 1 0 0 0 0 0 0

Nord-Trøndelag 21 82 349 0 4 39 17 3 0 0 0 0 0 0 0 0 0 0 0

Nordland 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Troms Romsa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0



C.7.9 HSR journeys (over 100 km) county-to-county matrix: Oslo-Stockholm (Karlstad) calling at Lillestrøm only: Scenario D 2024

County to/from

Østfold

Akers

hus

Oslo

Hedm

ark

Oppla

nd

Buskeru

d

Vestf

old

Te

lem

ark

Aust-

Agder

Vest-

Agder

Rogala

nd

Hord

ala

nd

Sogn o

g F

jord

ane

Mø

re o

g R

om

sdal

Sø

r-T

røn

dela

g

Nord

-Trø

ndela

g

Nord

land

Tro

ms R

om

sa

Fin

nm

ark

Fin

nm

àrk

u

Østfold 0 0 0 139 1 1 0 0 96 76 177 155 54 19 135 11 0 0 0

Akershus 0 0 0 286 36 51 139 21 1008 667 1515 1508 578 184 337 26 0 0 0

Oslo 0 0 0 2996 5 6 0 0 160 98 235 245 88 33 2431 222 0 0 0

Hedmark 142 293 3039 0 25 329 91 8 171 112 265 221 82 27 0 0 0 0 0

Oppland 1 36 5 24 0 0 1 0 45 31 70 54 21 7 19 2 0 0 0

Buskerud 1 52 7 324 0 0 0 0 0 0 0 0 0 0 307 25 0 0 0

Vestfold 0 141 0 90 1 0 0 0 0 0 0 0 0 0 122 11 0 0 0

Telemark 0 22 0 8 0 0 0 0 0 0 0 0 0 0 20 2 0 0 0

Aust-Agder 96 1016 164 172 45 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Vest-Agder 76 672 101 113 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Rogaland 177 1536 245 270 70 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Hordaland 161 1609 271 234 56 0 0 0 0 0 0 0 0 0 2 0 0 0 0

Sogn og Fjordane 56 609 94 87 22 0 0 0 0 0 0 0 0 0 1 0 0 0 0

Møre og Romsdal 19 195 35 28 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Sør-Trøndelag 137 344 2456 0 20 312 123 20 0 0 0 2 1 0 0 0 0 0 0

Nord-Trøndelag 11 26 219 0 2 25 11 2 0 0 0 0 0 0 0 0 0 0 0

Nordland 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Troms Romsa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0



Contact names: Michael Hayes Address: Euston Tower 286 Euston Road London NW1 3AT UK Email: [email protected] Telephone: +44 207 121 2388 Jim Millington Address: Euston Tower 286 Euston Road London NW1 3AT UK Email: [email protected] Telephone: +44 207 121 2414

© Atkins Ltd except where stated otherwise.

The Atkins logo, „Carbon Critical Design‟ and the strapline

„Plan Design Enable‟ are trademarks of Atkins Ltd.

Documents

Jernbaneverket Norwegian High Speed Railway Assessment …...Subject 1: Demand Forecasting Final Report 04/03/2011 (With additional information) Contract 5, Subject 1: Demand Forecasting