FACULTY OF CIVIL AND INDUSTRIAL ENGINEERING

Master Degree in Transport System Engineering

Thesis

High Speed Railway Project Development and

Regional Accessibility Improvement:

The First Experience in India

Supervisor:

Prof. Eng. Antonio Musso

Candidate:

Amal Kuzhiparambil Purushothaman

Co-Supervisor:

Dr. Eng. Cristiana Piccioni

N° 1722321

Academic Year 2018/2019

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Table of contents

Summary

1. Introduction

1.1 Study purpose

1.2 Research background

1.3 Research methodology

1.4 Key issues

2. The Reference framework

2.1 Definition of high-speed rail

2.2 HSR benefits

2.3 HS Rail around the world

2.3.1 Japan

2.3.2 Italy

2.3.3 France

2.3.4 Germany

2.3.5 Spain

2.3.6 China

3. The accessibility concept

3.1 Definition of accessibility

3.2 Accessibility indicators

3.3 A basic benchmarking exercise

4. Accessibility and HSR projects: an insight into international experiences

4.1 The Madrid-Barcelona HSR case study, Spain

4.2 The China HSR case study

4.3 The Seoul HSR case study, Korea

4.4 Brisbane - Melbourne proposed HSR, Australia

5. Building an accessibility indicators framework

5.1 Identification of Accessibility indicators

5.2 A selection of accessibility indicators

5.2.1 Weighted average travel times (Location indicator)

5.2.2 Economic potential

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5.2.3 Daily accessibility indicator

5.2.4 Economic accessibility

6. Pilot study: the Mumbai – Ahmedabad HSR project

6.1 HSR project background

6.1.1 Necessity of HSR System in India

6.2 Major cities affected by the project

6.2.1 Mumbai

6.2.2 Surat

6.2.3 Vadodara

6.2.4 Ahmedabad

6.3 HSR Project overview

6.3.1 Basic characteristics

6.3.2 Stations

6.3.3 Train operation plans

6.4 Accessibility assessment

6.4.1 Calculation and evaluation of indicators

6.4.2 Weighted average travel times (location indicator)

6.4.3 Economic potential

6.4.4 Daily accessibility indicator

6.4.5 Economic indicator

7. Lessons learned from a comparative analysis

7.1 Summary of pilot study

7.2 Comparative analysis with Madrid-Barcelona HSR ex-ante/ex-post evidences

7.3 Recommendations for adopting the selected indicators

8. Conclusions and Recommendations

8.1 Future research developments

List of Acronyms

List of Figures

List of Tables

References

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Summary

High-Speed Rail (HSR) is emerging all over the world as an increasingly popular and

efficient means of transport. After five decades of International experience developing

nations like India is investing in HSR infrastructure. Mumbai- Ahmedabad rail corridor

is the first experience in India. Benefits of such a huge investment are an issue of concern.

On this background, the thesis aims at understanding the project development and

regional accessibility improvement.

This thesis tries to provide a further contribution to the study of global HSR

networks. On this light, the thesis also includes a critical review of the Mumbai-

Ahmedabad HSR project in terms of functional and performance features. Further, this

aims to investigate on the regional accessibility enhancement achieved by the new

infrastructure.

In order to evaluate the accessibility improvement, this study put forward a set of

specific indicators derived from a benchmarking exercise. By analyzing from

international experiences, how well different types of accessibility indicators are able to

capture the accessibility changes. A set of accessibility indicators are introduced. Using

these indicators, relative changes accessibility of the study area are presented and

analyzed. The results provide an understanding of differential effects on regional

accessibility based on the geographical location and size of urban areas along the HSR

corridor under study.

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Acknowledgment

This project would not have been possible without the help of my advisers, so many

thanks to Prof. Eng. Antonio Musso and Dr. Eng. Cristiana Piccioni for the effort and the

time you gave to me.

I thank my family for their prayers and blessings for giving me the force during the whole

Master Degree, without you this would have never happened.

I thank my friends for their effort and help in completing my thesis.

Thanks to my University Sapienza University of Rome, and for each prof. who taught

me, Stefano Ricci, Antonio Musso, Guido Gentile, Mattia Giovanni Crespi, Paolo De

Girolamo, Paola Di Mascio, Gaetano Fusco, Massimo Guarascio, Gabriele Malavasi, Luca

Persia, and Liana Ricci.

I was one of the lucky students who had the honour of being taught under such

professors.

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Chapter 1

Introduction

1.1 Study purpose

Developing nations like India is taking its first step on High-Speed Rail (HSR) investment

after five decades of international experience. This paper is intended to review Mumbai-

Ahmedabad HSR project development and assess the regional accessibility

improvements.

An observation on the specific project details provides a better idea about the

quality of the system as a transport facility among the present international standard of

HSR networks. In addition, the thesis details the overview of HSR networks and the

socio-economic background of the region.

In order to evaluate the accessibility improvement, the project aims at developing

a set of accessibility indicators and methodology from identified best practices around

the world. Finally, the identified set of indicators are introduced in Mumbai-Ahmedabad

HSR and evaluated.

1.2 Research background

The quest for speed and growing impact of global warming to the transportation

industry are primary reasons behind the new HSR initiatives all over the world. HSR

project demands large scale investments so, the functional quality and ability to

perform as a transport system becomes a key concern.

Domestic transportations are an important factor for economic development.

Although India has a large and diverse transport network with its own challenges, they

can overcome by introducing energy-efficient technologies and improved performance.

India is the seventh largest nation with more than a billion populations, has a large

potential to invest in transport infrastructure

The concept of accessibility is used in many scientific research fields such as transport

planning, urban regional planning, feasibility studies, etc. Accessibility studies play a key

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role in policy making and give an important tool for understanding the economic

impacts. In addition, accessibility analysis studies address the link between the spatial

structure of the region and travel pattern of its residents. Therefore, it is very important

to identify a set of accessibility indicator that is closely related to the purpose of research.

1.3 Research methodology

The goal of the research is to evaluate the Mumbai- Ahmedabad HSR project

details and assess the regional accessibility improvement achieved. The study included a

global HSR framework, literature review on accessibility and accessibility indicator,

insights to international experience, case study background and project review, selection

of indicators and its calculation under case study data and evaluation of findings

obtained.

Various research techniques were applied in each stage of methodology. Firstly,

setting a reference framework for the study. Global statuses of HSR in some nation are

described, followed by the introduction of basic HSR details. The study chose Japan,

considering it as the pioneer in HSR transport. Four countries from Europe such as Italy,

France, Germany and Spain as a consolidated HSR system. Considering a new and

innovative system, Chinese HSR is also included in the study.

In a further literature review, the accessibility concept is introduced. Definition of

accessibility, accessibility indicators and supporting literature have included. Because the

focus of the thesis is to a find a set of indicators to initiate the case study, evidence from

international experiences are discussed in building an accessibility indicator framework,

four indicators are selected from the identified studies. The indicators selected are

weighted average travel time (location indicator), economic potential, daily accessibility

indicator, and economic accessibility. These indicators of technical and functional

characteristics are discussed.

In the background to the case study, the regional socio-economic and transport

scenarios are discussed. The current transport situation of the project affected cities

precedes the HSR project overview. Apart from the basic HSR characteristics, the thesis

focus on HSR stations and train operation plans to enlighten the accessibility analysis.

Next, the selected indicators are calculated using the collected case study data’s. A

comparative analysis with component modes and identified international experience

build further understanding of regional accessibility improvements.

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In summary, the general outline of the research is covered as per the above-

mentioned approach. The thesis report devotes to draft the research and finding with

explicit details, easily understandable structure, supporting maps and diagrams and

necessary references.

1.4 Key issues

Changes in transport infrastructure produce a progressive contribution of space

by shortening travel time and transport costs. The high-speed rail has the potential to

boost links between cities to a condition formerly unimaginable. Its competitiveness as a

mode of transport depends on the quality of service, access times to major economic

activities and potential to carry a large volume of passengers. As the HSR infrastructure

brings a large financial burden with it, its benefit is a major issue of concern.

The initial questions emerged alone with the objective of the thesis are the

methodology and level of the approach of the study. The HSR impact level and

limitations as an academic thesis were a matter of concern. Thus, the first challenge is in

defining between national, international or focused within an urban agglomeration level

of studies and appropriate methodology. The selection of methodology raises another

concern about data acquisition. As expensive onboard surveys are out of the reach of this

paper, the scope of GIS-based tools must be explored.

The selection of indicators is a core issue in measuring accessibility changes. In

fact, the result can be very distinct depending on the indicators used. Thus, defining and

selection of indicators kept as a matter of great concern in this thesis work. It is known

that is the conceptualization various the indicators respond differently and provide

complementary results of accessibility changes. So, selecting a set of indicators capable of

addressing all these concerns is a major issue needed to overcome.

Certainly, by overcoming these challenges the thesis kept setting a benchmark in

analyzing the regional accessibility improvements by HSR. In addition, the initiatives can

be successfully implemented for the case study also.

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Chapter 2

The Reference Framework

2.1 Definition of High-Speed Rail

High Speed Rail (HSR) can be defined as a rail service that can achieve faster

speeds than most of the conventional rail services due to better technical specifications

for horizontal and vertical alignment of the track, operating systems such as signaling,

and rolling stock. HSR has been sought after in various nations over Europe and Asia to

give enhanced mobility and trigger monetary advancement.

The vital factors that recognize HSR from ordinary rail in Europe & Asia include:

• Dedicated traveler lines with limited or no common use with cargo;

• Expansion of an HSR arrange that covers existing rail systems with established

demand;

• Use of city center stations that offer solid incorporation with other regional,

commuter, and metro/rapid transit networks;

• Use of established framework throughout the HSR system; and

• Use of electric traction to power rolling stock

The International Union of Railways (UIC) has developed a definition of HSR:

“High speed rail is a combination of a lot of elements which constitutes a whole

“system”: infrastructure (new lines designed for speeds above 250 km/h and in some

cases, upgraded existing lines for speeds up to 200 or even 220 km/h), rolling stock

(special designed train sets), operating conditions and equipment, etc.”

A high-speed system comprises of the following physical components:

1) Stations which are merged with local transport systems;

2) Track;

3) Civil infrastructure including earth work, bridges, tunnels, grade separations and

associated reconfigurations of existing infrastructure to prepare for the new

arrangement;

4) Facilities to perform and handle the framework and vehicles;

5) Systems including signaling, communications and associated electromagnetic

spectrum acquisition;

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6) Traction power; and

7) Vehicles.

High Speed Rail which is employed with the utmost commercial speed of 320km/h in

the world has been constructed by fusing various technologies which are contradictory

from the traditional ones. In order to avoid the huge losses that can occur in an accident

caused due to high vibrations of the rolling stock and to achieve safe high-speed

operation, progressively advanced technologies have been implemented. Numerous

technologies that are proven to be comparatively better such as the structure and

maintenance methodology of track, rolling stock, electrification system and Automatic

Train Control (ATC), etc. have been acquired to HSR.

Referring to the rolling stock, the technology development regarding running

resistance in high speed are, adhesion coefficient, running stability, power collection of

pantographs, bearing metal, wind pressure occurred when the train runs into the

passage, crossing of trains, and braking distance, etc. have been created. Rolling stock

which has aerodynamic shape and sophisticated body structure has been built up.

As to power, there is improvement of advances, for example, catenary structure

bearable for high speed, regular functioning and enforcement of its material,

compounding of catenary and installation of vibration reduction equipment to reduce the

vibration caused by high speed. Thus, proving the reliability of HSR.

Referring to signaling system, for instance, Automatic Train Control (ATC) which

displays signal on the indicator in the rail car (cab signal) and interlocks brake with cab

signal has been made and installed in order to accomplish high-speed operation, since

there is no scope for human blunder.

As listed above, various methodologies which include track, electric signal and

rolling stock, etc. has been introduced for the better results to achieve safe high-speed

operation. Thus, HSR system is one unique framework integrated with many advanced

technologies.

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2.2 HSR benefits

The very concept of HSR is intended in drastic betterment of economic growth.

Growth is observed in all fields such as tourism, employment, trade, transportation etc.

Benefits in terms of greater speed, improved safety, greater reliability, accurate frequency

were achieved. Cities were brought closer, thereby improving trade opportunities

between different markets, different people and different cities. It also attracted plethora

of tourists resulting in economic productivity.

Mostly operating at greater frequencies than conventional rail and having fewer

delays with improvised access to various destinations, HSR is considered as a savior.

Apart from a deadly accident in China in July 2011, high-speed rail operations have

maintained excellent safety records and had never experienced much injury or fatality.

In air and road travel restricted regions, HSR has come to the rescue. Shifting the means

of transportation to HSR has benefited passengers traveling for less than two and half

hours. The redirection of about 80% passengers from road and air trips to HSR added up

free space in conventional rail promoting cargo services, other intercity and commuter

rail services.

For instance, the United Kingdom has tended to limit requirements on its West

Coast Main Line with the execution of the proposed High-Speed line.

In Japan, the main motivation for implementing the Tokaido line between Tokyo

and Osaka was to provide additional capacity to the transportation network, rather than

to reduce travel times.

Employment, wages, trade in urban markets and output saw an immense boost in

regional and local economies. Improved working conditions, easy face to face

interactions, minimized cost of travel enabled labor to work efficiently and thus,

enhancing productivity, business competitiveness, leading to higher wages.

HSR gives more noteworthy ecological benefits and energy efficiencies than

different methods of long-distance travel. The natural benefits of fast rail rely upon a few

conditions: strong ridership, clean energy sources to power trains, and mode shift from

less efficient forms of transportation.

For example, Shinkansen trains are expected to utilize one-quarter the energy of

airplanes and one-sixth that of private automobiles per passenger mile. To achieve

environmental benefits, highspeed trains must increase load factors to realize the greatest

efficiencies.

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High-speed rail is the main accessible method of long-distance travel that does not

depend on motor fuels. It is powered by electricity, which is considered a better option

over petroleum generated power. Moreover, energy planning ensures the reduction of

greenhouse gases and other harmful pollutants.

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2.3 High Speed Rail around the world

2.3.1 Japan

Japan encountered a huge economic growth a decade after World War II. Initiating

the Tokaido-Shinkansen project was an evidence to it. it helped meeting the connectivity

demand in the densely populated areas of Osaka and Tokyo. Even during the 1950s, with

around 45 million people, the road and rail networks were congested. To address this

issue, Japan initiated its first HSR line in 1964, leading to the expansion of the existing

huge networks. The networks spread, multiplying the country's wealth eventually

resulting in economic growth.

Figure 1- HSR network of Japan (source: Japan Stations website)

The Tokaido line: The Tokaido line connected three main cities namely, Tokyo, Osaka and

Nagoya (approximately 30, 16 and 8.5 million inhabitants, respectively). It has recorded

that 5.3 billion passengers travelled between Tokyo and Osaka since 1964 and the

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Tokaido Shinkansen itself carried more than 10 billion passengers as per the report of

CJRC (Central Japan Railway Company report).

Serving 355 million

passengers annually,

Japan’s national high-speed

network today has a total

length of 3,041 km (1,890

miles). In a shorter time of

just two and a half hours,

the original line running

from Tokyo to Osaka, which

covers 515 kilometers (320

miles) is considered the

main transportation axis.

Shinkansen courses totally

on separate rail,

subsequently, not

influenced by slower nearby

trains or cargo. The

shinkansen utilizes

1435mm standard

measures and utilizes an ATC (Automatic Train Control) framework, eliminating the

need of trackside signals.

Tokyo- (operating kilometres) Osaka

(552.6 km)

Okayama

(732.9 km)

Hiroshima

(894.2 km)

Fukuoka

(1,174 km)

Travel Time (Shinkansen) 2 hr 22 min 3 hr 09 min 3 hr 44 min 4 hr 46 min

Number of services a per day

(Shinkansen)

250 128 99 67

Table 1

Figure 2 Japan HSR performance

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2.3.2 Italy

Italy is one of the pioneers in HSR industry who were the first to start such network in

Europe. Italian high-speed trains link country's major cities, with even more routes being planned

and under construction. Italy made it first step in the quest for speed in year 1939 itself. An ETR

212 set a record on an average speed over long distance between Florence and Milan with

maximum speed of 203 km/h. The foremost high-speed rail route in Italy, opened in 1977,

connecting Rome with Florence. The top speed on the line was 250 km/h, giving an end-to-end

trip time of about 90 minutes with an average speed of 200 km/h (120 mph). This line used a 3 kV

DC supply. High-speed service was publicized on the Rome-Milan line in 1988-89 with the ETR

450 Pendolino train, with a top speed of 250 km/h and reducing travel times from about 5 hours

to 4 hours. The model train ETR X 500 was the first Italian train to reach 300 km/h on the

Direttissima on 25 May 1989.

Figure 3 - Italy HSR map

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Passenger service is delivered by Trenitalia and, since April 2012, by NTV-Italo, the

world's first private open-access operator of high-speed rail to compete with a state-owned

monopoly. 25 million passengers voyaged on the network in 2011. In 2015, ridership increased to

55 million for Trenitalia and 9.1 million for NTV, for a combined 64 million passengers.

Trenitalia's high-speed trains are called Alta Velocità (AV), and are broken down into

three categories: Frecciarossa, Frecciargento, and Frecciabianca. Frecciarossa trains are the fastest,

reaching speeds of up to 190 MPH (300 km/h). Services on the high-speed lines is delivered by

Trenitalia and privately owned NTV.

The AV train network joins Turin, Milan, Bologna, Florence, Rome, Naples, and Salerno.

While Italo operates on a different set of rail lines, connects Turin, Milan, Venice, Padua, Bologna,

Florence, Rome, Naples, and Salerno.

Frecciarossa trains

Frecciarossa high-speed trains, operated by Trenitalia, reaches speeds of 300 km/h and

offer maximum comfort, making trips between Italian cities as short as possible. It makes more

than 120 daily connections throughout Italy, from Turin and Milan in the north, to Salerno and

Bari in the south. There are 28 non-stop Frecciarossa trains between Milan and Rome every day,

making the journey in just under 3 hours. Frecciarossa trains that stop on the way in Bologna and

Florence still make the trip in just over 3.5 hours. During peak travel times, there are 12 trains

leaving Milan to Rome and 13 leaving Rome to Milan.

There are 36 daily Frecciarossa trains between Milan and Naples, and that trip takes just

over 4 hours. There are 10 Frecciarossa trains between Turin and Rome daily, with stops in Milan,

Bologna, and Florence along the way. Frecciarossa trains make the connection from Bologna to

Florence 70 times daily in around 37 minutes.

The Frecciarossa 1000 is a deluxe environmentally-friendly option with the most

advanced technology available. It has 16 powerful engines and can reach speeds of 400km/h. The

train is also fully silent and has the certification of environmental impact.

Frecciargento trains

The Frecciargento trains links Rome to Venice, Verona, Bari/Lecce, Lamezia Terme /

Reggio Calabria on both high-speed lines and traditional lines. Frecciargento trains reach speeds

up to 250 km/h Rome – Venice – Rome: 26 daily connections in a 3 and half hours.

Rome – Verona – Rome: 6 daily connections. Out of that, 2 Frecciargento trains will

continue up to Brescia, allowing passengers to benefit from the recent doubling of the Bologna –

Verona line, and takes only 3 hours between Verona and Rome.

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Rome – Bari – Rome: 10 connections which makes only 4-hour journey.

Rome – Reggio di Calabria – Rome: There are 10 connections daily.

Frecciabianca trains

Trains offer service on traditional lines from Milan to Venice, Udine, Trieste, Genoa, Rome, Bari,

and Lecce. Frecciabianca trains can reach speed of 250 km/h.

Figure 4 - Major freccia High-speed line map

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2.3.3 France

Following the footsteps of Japan, France set its own HSR network. From 1970

onwards, France is kept on building HSR systems, the main line being between Paris

and Lyon. HSR standards of France such as gauges, voltage and signaling are

adopted by most of the European countries. Paris played a prominent role in the field

of business and politics. Efforts were being made to develop Paris, thus a rail

link connecting Paris and Lyon (the corridor to south-east France) became the

initial HSR service in France. The population of France was relatively low, and Paris

gradually emerged to be the central hub. The line expanded outwards from Paris to

connect other important destinations. It served various corridors in and around Paris.

Many European countries incorporated the French HSR standardizations. The

French rail operating company, SNCF, reports that its TGVs have taken the dominant

share of the air-rail travel market in many of the high-speed corridors, taking over 90

percent in the Paris-Lyon market. The total number of rail passengers raised

following its inauguration, rising from 12.5 million in 1980 to carrying 110 million

passengers per year.

Figure 5 - France HSR network

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2.3.4 Germany

Germany, the third nation to build up the HSR systems in 1991 and named its fast

trains as InterCity Express later became Intercity-express. Comparing the west-east

introduction of the rail network built before WWII and the current north-south patterns

of industrial cooperation, a decision has been made to change the network to

encourage cargo transportation from the northern ports towards the southern industrial

regions. Thus, the initial two new lines were those connecting Hannover and Würzburg

and Mannheim and Stuttgart, respectively. The principle objective was to determine

blockage issues in bound passages and to support north south cargo traffic.

Figure 6 - Germany HSR map (source: Transport Journal)

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German strategy is significantly different from the models embraced by Japan

and France, whose framework is connecting distant city-pairs with few intermediate

stops. The main idea is to upgrade existing rail lines providing more space with

higher speed service and simultaneously building new high-speed lines. From the

data available, the cumulative sum of passengers is roughly 1.25 billion in 2015.

Upgraded Line

Cologne-Aachen 250km/h

Partially new line

Hanover-Berlin 250km/h (new line) 200km/h (existing sections)

Nuremberg-Munich 300km/h (new line 200km/h (existing sections)

Fully newly line

Cologne- Frankfurt 300km/h

Hanover-Wurzburg 280km/h

Mannheim-Stuttgart 280km/h

Erfurt-Leipzig 300km/h

Lines not yet completed

Frankfurt- Mannheim 300km/h

Nuremberg- Erfurt 300km/h

Karlsruhe-Basel 250km/h

Hananu-Gelnhausen 300km/h

Stuttgart-Wendlingen 250km/h

Wendlingen-Ulm 250km/h

Table 2 - German HSR lines

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2.3.5 Spain

The first line was opened in 1992, connecting the cities of Madrid, Córdoba and Seville.

The Alta Velocidad Española (AVE) uses standard gauge. This permits direct connections to

outside Spain through the link to the French network at the Perthus tunnel.

Line Speed(km/h) Length(km) Start of

construction

Construction

completion

Madrid-Seville 300 472 1989 1992

Córdoba-Malaga 300 155 2001 2007

Madrid-Valladolid 350 179.6 2001 2007

Madrid-Barcelona 350 621 1995 2008

Madrid-Valencia 350 391 2004 2010

Albacete-Alicante 350 171.5 - 2013

Barcelona-French border 350 150.8 2004 2013

Valladolid-León 350 162.7 2009 2015

Valladolid-Burgos 350 134.8 2009 2016-2017

Seville-Cádiz 250 157 2001 2015

León-Gijon 350 - 2009 2017

Olmedo-Zamora-Galicia 350 435.0 2004 2011-2018

Murcia-Almeria 300 184.3 Unknown After 2018

Burgos-Vitoria 350 98.8 2009 2019

Basque Y 250 175 2006 2019

Mediterranean Corridor 250-350 >1300 2004 2013-2022

Madrid-Caceres-Mérida- 350 640 2008 After 2020

Table 3 Spain HSR lines

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By 2020, Spain should have connected almost all provincial capitals to Madrid in less than

3 hours and Barcelona within 6 hours with high-speed trains. The Spanish and Portuguese high-

speed lines have European standard and UIC track gauge of 1,435 mm and electrified with 25 kV

at 50 Hz from overhead wire. The first HSL from Madrid to Seville is equipped with LZB train

control system, later lines with ETCS.

Alta Velocidad Española (AVE) is a service of high-speed rail in Spain operated by Renfe,

the Spanish national railway company, at speeds of up to 310 km/h. Alta Velocidad Española As

of August 2017, the Spanish AVE system is the longest HSR network in Europe with 3,240 km

and the second longest in the world, after China's.

Three companies have built or will build trains for the Spanish high-speed railway

network: Spanish Talgo, French Alstom and German Siemens AG. Bombardier Transportation is

a partner in both the Talgo-led and the Siemens-led consortium. France will eventually build 25

kV TGV lines to the Spanish border, but multi-voltage trains will still be needed. To this end,

RENFE decided to convert 10 existing AVE S100 trains to operate at this voltage (as well as the

French signalling systems), which will cost 30 M€ instead of the previously expected 270 M€ for

new trains.

Figure 7 - Spain Rail Network map

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2.3.6 China

The HSR of china is most immensely used mode of transport in china. It is the

longest in the world and is designed for speeds of 250–350 km/h. the total length being

29,000 km, it covers 30 of the 33 provincial-level administrative divisions excluding

Macau, Ningxia, and Tibet. It plans to cover 38,000 km by 2025.

The HSR of China was planned back in the 1990s, inspired from Japanese

Shinkansen experiences. China Railway is the successor of the former Ministry of

Railways. The China railway corporation owns it, under the brand China Railway High-

speed (CRH). The CRH was launched in the year April 2007, consisting of two trains sets

namely, Hexie Hao and Fuxing Hao and later extended.

Figure 8 China HSR map

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Track network and major lines

China's conventional high-speed railway network is made up of four components:

• a national grid of mostly passenger dedicated HSR lines (PDLs),

• other regional HSRs connecting major cities,

• certain regional "intercity" HSR lines, and

• other newly built or upgraded conventional rail lines, mostly in western China,

that can carry high-speed passenger and freight trains.

Major High-Speed Rail Lines

Lines Open Date Length(km) Speed(km/h)

Beljing-Shanghal 30/06/2011 1,318 300-350

Beljing-Guangzhou 26/12/2012 2,298 200-300

Beljing-Xi’an 26/12/2012 1,216 250-300

Shanghal- Guangzhou 10/12/2014 1,647 250-300

Shanghal-Kunming 28/12/2016 2,252 300-300

Xi’an-Shanghal 10/09/2016 1,509 250-300

Xi’an-chengdu 30/09/2017 643 250

Inter-city High Speed Trains

Beljing-Tianjin 01/08/2008 119 300

Guangzhou-Zhuhai 31/12/2012 117 200

Guangzhou-Shenzhen 26/12/2011 116 300

Shanghal-Nanjing 01/07/2010 301 300

Nanjing-Hangzhou 01/07/2013 249 300

Table 4 China HSR lines

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Ridership

Since the initial journey of

an HSR train in China, annual

ridership has risen from 61.21

million in 2007 to 420 million in

2011, making China's HSR service

the most heavily used in the HSR

service market. In October 2010,

CRH service more than 1,000

trains per day, with a daily

ridership of about 925,000 as of

May 2015, a total of 1469 CRH

trainsets were put into use.

YEAR MILLION RIDERS

2013 672

2014 893

2015 1161

2016 1440

2017 1713

2018 2001

Table 5 China HSR ridership data

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Chapter 3

The accessibility concept

3.1 Definition of accessibility

The concept of accessibility is based on the premise that space constrains the

number of opportunities available; consequently, accessibility influences both the travel

costs and the levels of service use and participation in desired activities of people living

in a specific. There are wide variations in the definition of accessibility and the

appropriate definition always depends upon the intended application. Some fields of

application are: business or industrial location selections, travel demand forecasting,

population distribution and growth and transportation planning.

The following are well-known definitions of accessibility put forwarded by different

scholars:

o “The benefits provided by a transportation/land-use system”.

o “The ease with which any land-use activity can be reached from a location

using a particular transport system”.

o “The ease with which activities or destinations can be reached from a

certain place and with a certain transport system”

o “The extent to which land-use and transport systems enable (groups of)

individuals to reach activities or destinations by means of a (combination

of) transport mode(s)”

Based on their definition, certain components of accessibility can be identified:

The land-use component reflects the land-use system, consisting of: a) the amount, quality

and spatial distribution opportunities supplied at each destination; b) the demand for

these opportunities at origin locations; and c) the confrontation of supply of and demand

for opportunities, which may result in competition for activities with restricted capacity.

The transportation component describes the transport system, expressed as the disutility for

an individual to cover the distance between an origin and a destination using a specific

28

transport mode; included are the amount of time (travel, waiting and parking), costs

(fixed and variable) and effort (including reliability, level of comfort, accident risk, etc.).

This disutility results from the confrontation between supply and demand. The supply

of infrastructure includes its location and characteristics (e.g. maximum travel speed,

number of lanes, public transport timetables, travel costs). The demand relates to both

passenger and freight traffic.

The temporal component reflects the temporal constraints, i.e. the availability of

opportunities at different times of the day, and the time available for individuals to

participate in certain activities (e.g. work, recreation).

The individual component reflects the needs (depending on age, income, educational level,

household situation, etc.), abilities (depending on people’s physical condition,

availability of travel modes, etc.) and opportunities (depending on people’s income,

travel budget, educational level, etc.) of individuals. These characteristics influence a

person’s level of access to transport modes and spatially distributed opportunities.

In essence, considering these concepts, in this research project, accessibility is

defined as follows:

“Accessibility is the ease with which individuals can reach a destination from a certain

place within a region and with a certain transport mode”

Accessibility must be considered in parallel with the concept of mobility. While

mobility is concerned the performance of transport systems depends widely on

accessibility. Accessibility measures are thus capable of assessing feedback effects

between transport infrastructure and modal participation. Some accessibility measures

also include behavioral determinants for activity patterns in space and time, and the

responses of transport users to physical conditions.

The time when accessibility explicitly takes on board, the land use-transport

connection, handles trip numbers and travel time were used as indicators. Later on, the

multiple components of accessibility, accessibility can be measured in different ways.

Accessibility can be measured by different ways on the individual level (person-

based), or at the location level (place-based). Whereas person-based metrics focus on the

29

individual component, place-based metrics mainly account for the land use and transport

components. The individual component is sometimes included in location-based studies

by stratifying population by age group or socio-economic characteristics, and by

segmenting destinations (by job types for example). Location-based metrics typically

accounts for the number of opportunities that can be reached from a specific location,

based on the travel costs to destinations using a specific mode. Location-based

accessibility is most commonly used by policy-makers as it provides a comprehensive

measure of the land use and transport system at the regional level and so in this study

also.

3.2 Accessibility indicators

In order to have strong positive public support for huge investment required for

the conceptualization, planning, development and operation of HSR project, it is

important to fully grasp the contributions by HSR towards transportation, economic,

environmental, social and wider regional impacts in the HSR corridor, region and

beyond. However, because of the difficulties in quantifying some of these impacts,

justification is always an ambiguous one. Thus, the explicit indication of accessibility

improvement is important tool for decision makers.

Accessibility impacts of a new transportation system is measured by means of a

wide variety of accessibility indicators. These indicators reflect the numerous approaches

to the concept of accessibility as discussed, several existing studies. Accessibility

indicators are based on different accepts such as location of an area with respect to

opportunities, activities or assets existing in other areas and in the area itself, where ‘area’

may be a region, a city or a corridor.

Most accessibility measurements combine travel impediment and attractiveness of

different destination. Travel impediment is usually expressed in different cost units such

as distance, travel time or generalized cost of transport that combines travel time, travel

cost and other travel dis-utilities. Attractiveness of urban agglomerations depend on their

masses such as population, employment or gross domestic product (GDP).

Accessibility indicators differ in complexity. More complex accessibility indicators

take account of the connectivity of transport networks by distinguishing between the

30

network and the activities or opportunities that can be reached. These indicators always

include in their formulation a spatial impedance term that describes the ease of reaching

other such destinations of interest.

Further in this study, considering the data availability, the easiness in results

interpretation and communication, level of study and research objectives different

accessibility indicators are identified and discussed in the following chapters.

31

3.3 A basic benchmarking exercise

Benchmarking is the process of comparing the existing practices, identifying the

best one and adopting well-defined improvements to enhance the performance.

Benchmarking is also important to policy makers seeking to improve the performance of

an HSR system.

In this thesis, the idea of benchmarking is initiated to put forward a set of

accessibility indicators focusing on HSR service accessibility comparison to other modes

at regional level. Accessibility measurement studies conducted all around the world for

feasibility studies, urban planning or research objectives are using wide variety of

indicators. Parameters such as travel time, distance, location and socio-economic

variables are used in many indicators in different ways and results in indicating different

focus. For example, the same “travel time decay” is used in daily accessibility indicator

and economic potential in different manners, with and without distance decay.

Furthermore, most studies use more than one indicator. So, a proper selection of

indicators is relevant, so as to define an assessment framework consistent with the aims

of this thesis work. More precisely, a benchmark exercise has been carried out to identify

a specific set of indicators best fit to the research objectives, gain necessary performance

increase as well as to understand accessibility improvement achieved by HS rail

compared to other transport modes in competition.

32

Chapter 4

Accessibility and HSR projects: an insight into international

experiences

4.1 Madrid—Barcelona HSR case study, Spain

The accessibility impact study of the high-speed line Madrid-Barcelona-French

border covered both the national and European level. A geographic information system

(GIS) and detailed surveying is used to carry out this study.

Selected Indicators: Three specific indicators are used in order to measure accessibility

impact, which respond to different conceptualizations and offer complementary

information to the problem of changes in accessibility. They are respectively: Weighted

average travel times; Economic potential and Daily accessibility indicator.

Study Area: The Highspeed line connects Madrid- Zaragoza – Barcelona of the Spanish

high-speed network.

Figure 9 - The European high-speed network in the study area: scenario 2005.

33

Travel time savings: Direct travel time savings along the HSR line, the new HSR line saves

2-hour 48 min in direct comparison with other competitive modes. From 5-hour 28 min

to 2-hour 40 min, it is of 51.2 % of saving in total travel time.

Routes Travel time, 2005 Travel time saving

Without new line With new line Absolute %

Madrid-

Barcelona

5 h 28 min 2 h 40 min 2 h 48

min

51.2

Madrid–

Zaragoza

3 h 3 min 1 h 25 min 1 h 38

min

53.5

Zaragoza -

Barcelona

3 h 27 min 1 h 15 min 2 h 12

min

68.6

Table 6 – Change in travel time (source: Gutierrez 2001)

Weighted Average travel time: The weighted average travel time is calculated not only for

the cities along the line but also for many European agglomerations in the study area

(those with more than 300,000 inhabitants). Logically, the greatest benefits is for cities

along the HSR line, and the study also accounts those cities better access with each other

and to the cities in the rest of Europe.

Figure 10 - Weighted average travel time change in the study area, Spain

34

The new line brings reduction of 25 minutes that is about 5% of the average travel

times between all the selected urban agglomerations. The populations which obtain the

highest time savings is Zaragoza with 160 minutes of average travel time, that is up to

22%. Table 3 also shows large benefits for Barcelona (17.8%), Madrid (13.7 % of time

saving) and other cities directly at the new HSR lines serving area.

Economic potential: From the economic potential value calculated for many cities in the

study area, the average variation in economic potential of the selected urban

agglomeration (only with increase of 1.45%) is much less than the one which

correspondence to location indicator (average travel time reduced by 5%). The table

shows the European cities located far from the new line undergo very little variation in

their potential values. In fact, changes in the accessibility are mostly concentrated on cities

which are directly connected to the new line than the location indicator. As shown the

city that most benefit from new HSR network is the city Zaragoza (37%), which is situated

close to too large populations such as Madrid and Barcelona and above that,

comparatively less benefits for Barcelona (16%) and for Madrid (8%). Furthermore, the

trend points out to the benefits of the cities in Spanish sector as not only from better

connectivity with Barcelona, also the improved connectivity with most of the European

cities located beyond the French boarder.

Daily accessibility: The average accessible population within the 4-hour travel time limit

for the selected cities shows rise about a million inhabitants in average. From 20.7 million

to 21.1 million inhabitants, which means an increase of 1.64%. This values from the table

indicates rise of average number of accessible inhabitants of each city in travel time limit.

In fact, the daily accessibility indicator has a very concentrated effect. The rise in total

accessible population is important in Barcelona, total of 7.7 million inhabitants and 139%

rise, which corresponds to the nearest urban populations such as Madrid, Valladoid and

Marseilles.

Key findings: On accessibility improvements, the effect of new HSR line relevant not only

in Spanish region that connected by the HS rail, but the study also extents to the effect on

the Iberian Peninsula.

In conceptualization, the three indicators have used a different approach. When

the location indicator (Weighted average travel time) focus over relationship over long

distances and simultaneously, the daily accessibility indicator emphasis the relationships

35

over short distances. Logically, the results are quite different: very concentrated effects

for daily accessibility indicator, less concentrated in economic potential and relatively

more dispersed in the location indicator.

36

4.2 The China Railway High-speed Network

China’s large-scale HSR network has significantly high influence on both

accessibility and connectivity. Changes in connectivity largely affect the external relations

among cities, recently China has invested in transport infrastructure have much focus in

HS rail connectivity. Thus, here examines the impact of China’s HS rail network on the

overall connectivity and model centrality of the city network, as evaluated by passengers’

trains from 2009 to 2013

Study area: Researchers have applied accessibility to examine efficiency or

economic gain HSR impact studies in China. It has calculated the accessibility effects of

HSR for 2009 and 2013 and reported huge benefits to the cities connected with HSR and

cities in the prosperous customer region than that of non-HSR cities and cities in the

hinder-land did. One of the mostly discussed issues is HSR station locations HSR stations

in Chinese cities are mostly situated outside the city core area in sub urban or even rural

areas. This requires an extra link to the cities and also results in the decentralization. The

following study on accessibility of Chinese HSR and the selection of indicator should

focus on these issues also.

Figure 11 Study area map, China

Accessibility indicator and methodology: The study applies a commonly used gravity

model for measuring accessibility. It takes the following form.

37

AiY = ∑ 𝐸𝑖

𝑦

(𝑇𝑖𝑗𝑌)𝛼

Value A represent the accessibility of city j, Ej measure the destination

attractiveness at location j and T is the travel time by rail between origin in j and

destination of j, Y denotes the year in which A is measured. The parameter α reflects

traveler’s sensitivity to travel time increase its value is generally calibrated from travel

surveys and here took as 1.

Accessibility growth from 2006 to 2014 can be influenced by both reduced rail

time and increased jobs. As the objective of the study focus, the independent effect of

HSR on accessibility should be accounted. Two accessibilities are calculated. Other than

base accessibility, an accessibility of the cities using 2006 data for employment but with

2014 rail times is also calculated. So, the difference between the estimated and the base

value can be referred as the contribution of HSR.

The accessibility improvements are calculated using the above-mentioned

indicator for four territorial regions such as Eastern China, Central China, Western China

and North Eastern China consisting of 19 cities nation-wide.

Key finding: From the results obtained from calculating the above-mentioned indicator, it

is evident that the accessibility increased from 2006 to 2014 nation-wide (186.2%), in four

territorial regions and in all 19-city cluster. Four regional clusters show more than double

increase in accessibility scores. Within the territorial region, cities show varying levels of

gains in accessibility. The region that experienced lowest increase in accessibility is

Tianshan Northridge (85.7%), because of its remote location and comparatively less

population and economic concentration. Similarly, the highest improvement in

accessibility in this period is for central china with 206% of rise. It is clear that the central

plain consist of regions like central Shangxi and central plain, relatively developed and

populated. But the individual city in the study area with highest increase is North Bay

(240%) and this region has high urban population concentration. The cities, like Nnning,

Venue of Asean expo, with two third of its population focused on cities includes in the

North Bay region. It is evident that the indicators are reflecting these scenarios.

Accordingly, researchers adopt different approaches for better understanding of

the indicators. Mapping the accessibility scores of cities cluster to visualize the spatial

patterns of accessibility associated with HSR. Second, calculation of co-efficient of

38

variation to examine the potential effect of HSR on within-region disparity. Third, to

better understand the role of HSR separated from the effects of economic growth,

decomposed the observed changes in economic growth effect and other effects.

In summary, the Chinese study shows facts that, HSR improved travel time not only for

cities located on HSR lines but also for the non-HSR cities owing to HSR’s network effects.

The magnitude of accessibility varied HSR shrinks time space and makes remotely

located opportunity distribute unevenly over the space throughout the country. As China

plans to expand its HSR network to connect to connect more cities, it is timely important

to research on ways to integrate plans for HSR routing and station siting with regional

spatial development plans in order to avoid overheating and over-investment in HSR

infrastructure.

39

4.3 The Seoul HSR case study, Korea

Study area: The Korea Train eXpress (KTX) became operational in April 2004, it is evident

that the high- speed inter-city service has been creating positive impacts on forming a

model share structure comfortable to the notion competitive advantage between travel

modes. The increase in ridership is generally accepted as the influence of accessibility

improvement also. Here, the systemized accessibility analysis with a case study of the

Seoul metropolitan area is stated. It is the area covering 12% of total national area (11,753

km2) and of 46% of national population with a population above 25 million and is fifth

largest metropolitan area in the world.

Figure 12 - Seoul case study area

Indicators and Methodology: For measuring accessibility either conventional or log sum

type measure can be used, but this approach is carried out with developing a modified

Hansen type index to investigate the accessibility of Korean high-speed rail. Thus, by

40

eliminating the surveying and other data acquisition, difficulties if log sum type

measures over the conventional indicators.

Accessibility Aj at original j directly varies with the opportunity S of the socio-

economic activities of destinations j and inversely with transport costs can be written as:

Aj =∑ f-1 (Cij)

and by fixing the socio-economic opportunities and formulating the cost as a linear

function of the attributes of trips weighted by their parameters. The assessment is to

quality the degree of accessibility of different geographic regions.

The assessment has broadly 5 stages. First, the patronage of KTX of each origin

zone is plotted against the zonal accessibility. The data of ridership collected from the

survey is used with generalized cost of the location to measure the accessibility. Second,

a function which best fits with the obtained observation is drawn. Then, third, an

ANOVA test (Analysis of Variance) is applied to classify the high-speed rail impact

boundary of zones. The boundary is set as high, medium or low in ridership and good,

fair or poor is zonal accessibility as being a set of acceptable criteria for the accessibility

analysis. Fourth, the point of tangency between the loci of the decay functions and impact

boundary determines the zonal accessibility. Thus, each observations accessibility and

ridership’s are evident. The unit of measurement has normalized patronage that was

defined as the demand divided by population. Finally, a mapping audit is conducted. In

particular, a GIS-based approach is adopted because GIS is a visually appealing and cost-

effective tool in which many different data sets can be easily displayed in single or

multiple layers.

Key Findings: The Figure 13 that shows the ANOVA test plotted for the ridership and

accessibility. These directly give the classification of KTX impact boundaries and degrees

of accessibility. The summary of the data also gives idea about observations fall in each

category and the corresponding values. Here,20 observations fall in high and 25 in

medium and 23 in low, the unit of measurement is the normalized patronage that was

defined as the demand by population.

41

Figure 13 - Test result, Seoul case study

Summary of data

Boundary Count Sum Average Variance

High 20 203.37 10.17 12.21

Medium 25 120.23 4.81 7.94

Low 23 39.27 1.71 1.06

Table 7 – key findings, Seoul case study

Figure 14 shows the accessibility classification of the region. It is evident in the map that

the good accessibility region consists of Seoul and some Gyonggi province areas in the

southern region of the Seoul metropolitan area. This area leans to South. Specifically,

North Seoul is excluded and but some regions of Gyonggi; province regions are included.

42

Figure 14 - Accessibility change plotted on study area

Further, when connecting the GIS mapped data to ridership measure from the test

results and economic status of the region (Korea National Statistical Office Data), many

observations can be put forwarded. Such as the accessibility of North West Gyonggi is

not poor, but the ridership is not at a corresponding level. Again, this would be the result

of economic power of the residents in this area (KNSO data). Observing such socio-

economic scenarios in correlation with test result can provide trends and beneficiaries.

Thus, the study measures the accessibility and plot the connection under lies with the

rider potential and regional economic status to it.

43

4.4 Brisbane – Melbourne proposed HSR, Australia

After the successful contribution of HS rail to global transport connectivity in

Japan, Europe and China, Australia has been under investigation since 1980s.Many

studies has conducted at regional and national level on the accessibility improvement can

be achieved through HSR network. An ex-ante analysis on the regional accessibility

improvement is stated as follows:

Proposed HSR alignment and study area: The linear alignment shown in figure x is used to

assess the regional accessibility impacts of the proposed HSR system. This alignment is

proposed by AECOM et al. The proposed HSR alignment connects four Australian

Eastern States (VIC, ACT, NSW and QLD) and their capital cities (Melbourne, Canberra,

Sydney and Brisbane) respectively in a linear network fashion. Australian HSR system is

expected to be capable of operating speeds of up to 350km/hr. The Australian HSR system

will take maximum of 6 hours travel time from Melbourne to Brisbane. It will take only

about 3 hours from both Melbourne to Sydney and Sydney to Brisbane. Canberra will be

an hour travel time from Sydney and 2 hours from Melbourne.

Sydney and Brisbane are large cities (more than 1 million population) and

Canberra, Newcastle and Gold Coast are intermediate cities (more than 300,000

population) on Australian HSR alignment. The major regional towns in Australian HSR

corridor are Shepperton, Albury Wodonga, Wagga, Goulburn, Bowral, Gosford, Taree,

Port Macquarie, Coffs Harbor, Grafton and Lismore/Ballina/Casino.

Selected indicators: For the purpose of this analysis, four accessibility indicators are used.

They are respectively: location indicator, economic potential indicator, daily accessibility

indicator and commuting accessibility indicator. These indicators respond to different

conceptualizations and offer complementary information about the issue of accessibility.

These selected accessibility indicators are calculated for year 2011 for three competing

transport modes, such as roads, conventional rails and proposed HSR to predict the

accessibility improvements come from the proposed Australian HSR system. The

accessibility calculation needs both transport network data (e.g. travel time, travel costs)

and attractiveness or mass (population) of the urban agglomerations. The cities in the

research area with a population of higher than 20,000 inhabitants where the proposed

HSR stations located are included in the study. Similar data of these cities were collected

44

from official population census statistics of Australia. Each indicators and research

findings are discussed here:

Figure 15 - Proposed Australian HSR layout

Location Accessibility Indicator: From the calculated results, it is evident that the

intermediate towns show more improvements in location accessibility than the larger

cities at the both ends. The analysis shows that Australian HSR will improve the location

accessibility of all cities the HSR connects by minimum of 65% in comparison with

existing ground transport system. It is also clear that the location accessibility changes for

all cities will be similar, however, outlying regional areas such as Shepperton, Canberra,

Gosford, Lismore and Gold Coast will have better location accessibility increase than

other areas.

Economic Potential: Improvement in economic potential is very high and evident

comparing with the previous indicator. The study shows that Australian HSR will

45

improve the economic potential the cities from 200% to 320% compared with maximum

population reached per unit of time by existing efficient ground transport system (i.e.,

roads). It also shows that the Australian HSR will improve the economic potential of the

regional towns such as Shepperton, Wagga Wagga, Gosford and Lismore more than large

capital cities and other nearby regional agglomerations.

Daily Accessibility: In terms of daily accessibility indicator, almost all the cities show

double the improvement in the number of people. It is also clear that the remote regional

towns (Albury-Wodonga, Wagga Wagga, Canberra, Port Macquarie, and Coffs Harbor)

are the highest beneficiaries of the daily accessibility improvements. Moreover,

Sydneysiders will be able to reach all population within the HSR corridor within 3 hours

of one directional travel (i.e., daily accessibility). Moreover, Australian HSR will result

two bands of daily accessibility regions: Melbourne to Sydney (southern HSR daily

accessibility region with catchment of ten million people) and Sydney to Brisbane

(northern HSR daily accessibility region with catchment of 8 million people).

Commuting Accessibility: The study shows that commuting accessibility of peripheral

regional towns (Shepperton, Goulburn, Bowral and Lismore) associated with three large

cities (Melbourne, Sydney and Brisbane) will improve significantly. Australian HSR will

result three bands of commuting regions: Melbourne to Shepparton (southern HSR

commuting region with catchment of 4 million people), Canberra to Newcastle (central

HSR commuting region with catchment of 5 million people) and Lismore to Brisbane

(northern HSR commuting region with catchment of 3 million people).

Expected Findings: All the four indicators show that the proposed Australian HSR system

will significantly improve the regional accessibility of all urban agglomerations by

bringing them closure to each other compared with the existing accessibility. However,

the peripheral regional towns to three major cities in Australia are the biggest winners in

terms of regional accessibility change. Improvement in the regional accessibility of the

urban agglomerations along the HSR corridor is one of the major benefits of Australian

High-Speed rail network as the accessibility improvements are proved to have positive

impacts on regional socio-economic development.

46

Chapter 5

Building an accessibility indicators framework

5.1 Identification of accessibility indicators

In chapter 4, a selection of past experiences concerning HSR accessibility

assessment have been presented. One is from Europe, two from Asia and the last one

comes from Australia. Each study varies from each other in their level of approach, study

area, conceptualization of indicators, data required, data collection method and

representation of main outcomes. All the factors mentioned in Chapter 4 have been

considered in this thesis work in order to formulate a set of indicators and approach best

fit for the Indian case study.

Study area: The project under study is the part of regional network of Indian

railway between Mumbai and Ahmedabad. So, the selection of indicators gives

prominence to regional level approach. Among the identified studies in Chapter 4, Seoul

and Australian cases are more regional level than the other two. On the other hand,

studies focusing on such as China and Spain cases, cover a more national and

international level of. Besides, both studies focus a network instead of a single line

connecting two cities.

Indicators: The use of indicators help in scientific identification, quantification and

ranking of area with varying degrees of accessibility. Generally, most of the studies use

gravity model for measuring accessibility as in the case study of China. In the case study

of Soul metropolitan area, as detailed in previous chapter, a modified form of

conventional indicators is used. Both such cases, the indicators combine two components,

the impedance and locational attractiveness. While in other two studies multiple

indicators are used. Moreover, some indicators used in Spain and Australia case studies

are quite similar. This helps in understanding the flexibility of indicators in addressing

different scenarios.

Data collection: Data required, and possible methods of data collection are

important while identifying indicators. Conducting surveys as well as processing large

amount of data is a heavy task. Reliability and quality of the data is also relevant. Case

studies previously discussed suggest that the use of GIS based tools in data acquisition

47

along with regional socio-economic statistics is a well-known and widely accepted

practice. In most cases, data like population and other economics attractiveness can be

projected from the last census.

Illustration method: Each assessment study provides a large scale set of information.

However, if information is not easily grasped with implication, it will be ignored or

potentially misinterpreted. This results in slow, poor or uninformed decision-making

process. According to the four studies discussed above, the best way of illustrating the

result is projecting the calculated values into a map along with measured accessibility

values. This method gives faster understanding of the values in connecting with

corresponding regions, thus enabling easy comparison among different scenarios. In the

Seoul case study (section 4.3) results provide an accessibility assessment in connecting

with ridership. However, such results cannot be represented in a single map and in such

case the analytical complexity increases accordingly.

International experiences described in Chapter 4 shows the usage of several

indicators such as conventional gravity models, modified Hansen type, location

accessibility indicator (weighted average travel times), Economic potential and daily

accessibility indicator. Besides, other relevant measures such as Economic accessibility

and Global accessibility are also discussed. The Global accessibility concept can be

partially covered through the location indicator.

As the intention of this study is to measure the accessibility improvement at

regional level, not to calculate the possible catchment areas of the infrastructure, the

global accessibility indicator can be intended as out of scope. Further, the indicators in

the case studies use economic activities only as a function to represent the economic

attractiveness for example the use of population in economic potential or location

indicator. Thus, an economic indicator with direct depiction of economic values provide

better understanding.

According to what experienced in the selected “good practices”, taking into

account the dataset built through a focused data collection along with the main purpose

of this study, three specific accessibility indicators have been chosen, as follows: : Location

accessibility indicator (Weighted average travel times), Economic potential and Daily accessibility

indicator along with economic indicator. Such indicators will be further investigated in

the following chapters and then used in the Mumbai- Ahmedabad HSR case study.

48

5.2 A selection of accessibility indicators

In this chapter all the selected indicator is discussed with corresponding

formulations. The concept of each indicators and differences in the result are also

discussed in the following sub sections. The discussion is elaborated with reference to the

case studies listed along the chapter 4. The discussion is developed by understanding

each indicator individually and comparing among selected indicators also.

5.2.1 Weighted average travel times (location indicator)

The weighted average travel time between each node and all urban

agglomerations is calculated taking as weight the mass of the centers according to the

following;

𝐿𝑖 =∑ (𝑇𝑖𝑗. 𝑀𝑗)𝑛

𝑗=1

∑ 𝑀𝑗𝑛𝑗=1

Where Li is the accessibility (location) of node i, Tij is the travel time by the minimal-

time route through the network between node i and all urban agglomerations is used as

weight to value the importance of the minimal-time routes. The measure is not a gravity-

based indicator (there is no distance-decay), so that, unlike economic potential it does not

place the emphasize on short distance. Thus, for example, in the economic potential

model, discussed in the Spain case study, the relationship Madrid-Guadalajara could

weigh more than the relationship of two potentially larger cities Madrid and Paris,

because Guadalajara is very closer to Madrid than Paris. This average-distance-based

indicator should be interpreted from the locational rather than the economic point of

view. But economic implications are obvious, since the spatial situation of the regions

within country is a factor of attractiveness and development capabilities of the region.

This measure expresses the relative location of each place and the extent to which a new

link modifies this location by reducing access time to the main urban agglomeration. The

results are very easily interpreted, for example: from node A the average travel time to

all centers is 400 min in the scenario “without the line” and 360 min in the scenario “with

the line”, which means a time saving of 40 min.

5.2.2 Economic potential

The economic potential is a gravity-based measure, widely used in accessibility

studies. It is a measure of the nearness or accessibility of a given volume of economic

49

activity of a particular point/region and can be interpreted as the volume of economic

activity to which region has access, after the cost/time of covering the distance to that

activities have been accounted for. According to this model, the level of opportunity

(accessibility) between a node i and a destination node j is positively related to the mass

of the destination and inversely proportional to some power of the distance between both

nodes. Its classical mathematical expression is as follows:

Pi= ∑Mj

Tij

𝑛𝑗=1 a

Where Pi is the economic potential of node i, a is a parameter reflecting the rate of

increasing of the friction of distance (distance decay) and the other terms are still known.

In this paper (as in most accessibility studies) the parameter values a used is 1. Using

higher values than 1 means giving too much importance to relations over short distance

(which would not seem appropriate when analyzing the effect of a new infrastructure of

a national nature such as the line which is the object of this study) and it also means

increasing the problem known as self-potential.

When discussing the former indicator (Weighted average travel time), it has been

argued that in the evaluation of the impact of large transport infrastructure it would

seem reasonable to point out the long distance effect. Yet from a merely economic point

of view, there is doubt that the economic effects of a new infrastructure are inversely

related to the distance (there are many trips over short distance and few trips over long

distances), so that in this context it would seem appropriate to use a gravity-based

operationalization. Therefore, the interpretation of the result provided by this indicator

must be carried out from an economic view point; the indicator measures the economic

potential of each place in each of the scenario considered and the change in potential

caused by the new infrastructure true.

5.2.3 Daily accessibility indicator

This indicator consists of calculating the amount of population or economic

activity that can be reached from a node within a certain travel time limit. The time limit

is usually established in 2 or 4 h, so that it is possible to go and return the day and carry

out an activity at the visit location. The limit of 3 h travel is considered as a critical cut-

off point since it represents the likely limit of comfortable day return business traffic,

although the limit of 3 h is the likely cut-off point for major transfer from air to rail

50

transport. The travel time limit is set by considering the level of study and project

background.

This measurement is particularly useful for calculating accessibility in business

and tourist trips, for the need to stay overnight in the destination city means an important

extra expense for both companies and individuals. In fact, the empirical evident shows

that new high-speed lines produce an increase not only in the number of travelers in the

relations served by the line, but also in the proportion of those who return within the

same day.

In the context of the high-speed train, this indicator provides basically the

number of possible business contacts (for business trips) and the market potential (for

tourist trips). It measures how much population can be reached from a place (or can reach

a place) in a certain travel time limit and the changes in accessible population brought

about by a new infrastructure. The results are of the following type: from city A, within

a travel time limit of 2 h, 10 million inhabitants can be reached in the scenario “without

the line” and 15 million in the scenario “with the line”, which means an increase of 5

million inhabitant.

5.2.4 Economic Indicator

There is no doubt that the mode choice has greater influence of force in accessing

an infrastructure. When a user makes a mode choice decision, his perceived cost includes

the money value along with time and other monetary costs he needs to pay for the trip.

On accessibility issue, the fare of the trip can consider as an indicator of accessibility study

primarily of this reason. And, the fare of HSR or any other modes is easily available and

as it is directly in money value, the results are easily understandable too.

Considering the fare as an indicator, the willingness to pay and economic

condition of users are should be accounted. Willingness to pay is the amount that an

individual is willing to sacrifice to procure the transportation service. These facts highly

influence on mode choice. So, the users’ behaviour on mode choice is influenced by

willingness to pay and it highly depends on the income of passengers. Thus, the service

offered is not only judged by quality of the service but also the capability of service users.

Therefore, along with the fare, the income level also should be accounted. The GDP or

GDP per Capita values can be analysed on this context.

51

As an indicator of accessibility, a comparison of fare with other available modes

is also an important aspect. An HSR line should be able to provide service at acceptable

fare to a particular class of users the transport system is targeting. Thus, in this case study

includes comparison between different modes and a cross country comparison of fare.

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Chapter 6

Pilot study: Mumbai – Ahmedabad HS Rail project

6.1 HS Rail project background

Transport infrastructure plays a key factor for the development of a country. One

cannot over emphasize the importance of transportation than call it the 'lifeline' of a

nation. Everybody is looking forward for fastest and efficient means of transport

infrastructure for transportation. Good physical connectivity in the urban and rural areas

is essential for economic growth. India, the seventh largest nation with over a billion

population, has one of the largest transport sectors among the world.

Domestic transportation is a key factor for economic growth and transportation

issues and infrastructural delays affect a nation's progress and India needs much faster

and efficient transportation systems.

6.1.1 Necessity of HSR System in India

Rail transport systems is one of the most efficient and more economical means of

transport than road. Also, Rail construction costs are lower than road for comparable

levels of traffic. Historically, the Indian railways have played a leading role in carrying

passengers and cargo across India’s vast territory.

There are several strong arguments and reasons which support the introduction of HSR

in the country. In the year ending March 2018, IR carried 8.26 billion passengers and

transported 1.16 billion tons of freight. Apart from diverting passengers from road and

air, HSR generates a new class of passengers as well. With the average operating speeds

of around 250 km/h, HSR helps bring settlements 500 km apart within two hours of each

other. By Rail Experts, HSR has been a catalyst for economic growth, a stimulus for the

development of satellite towns, helping alleviate migration to metropolises. Providing

services from and to city centers, HSR serves important centers in route, providing value

for time through express and easy access to tier-II and tier-III cities.

53

As per JICA survey, Indians travel more and longer distance. By 2020-21, Indians will

travel on average thrice as much as they travelled in 2000-01. There are a lot of commercial

and industrial establishments over the country. The introduction of HSR is a key facility

that is likely to cut down on time and cost of travel across key financial sectors or links.

This in turn will make way for more investments and enterprises and generally boost

“Make in India” initiatives. One of the key concerns in recent times is the high rate of

unemployment in the country. Introduction of HSR will generate employment by the

thousands, particularly in cities such as Pune, Surat and Ahmadabad, where

manufacturing industries are rapidly growing.

Figure 16 - Mumbai-Ahmedabad HSR map

54

6.2 Major cities affected by the project

The Mumbai - Ahmedabad HSR project connect four major cities of the region

such as Mumbai, Surat, Vadodara, and Ahmedabad along with several intermediate

cities.

Figure 17 - Population density in the project affected area

55

6.2.1 Mumbai

Mumbai is the most populated city of India and estimated about 12.4 million

people. Mumbai account for slightly more than 6.16% of Indian economy contributing

10% of factory employment, 30% of income and 40% of foreign trade like most of the

metropolitan cities. Mumbai has a large influx of people from rural area looking for

employment.

Socio Economic Facts

Population in 2011 (2001)

Mumbai City 3,145,966 (3,326,837)

Mumbai Suburban 9,332,481 (8,587,000)

Greater Mumbai (Total) 12,478,447 (11,913,837)

MMR 20,748,395 (18,414,288)

Decadal Growth Rate (%)

Mumbai City (-) 5.75

Mumbai Suburban 8.01

Greater Mumbai (Total) 4.74

Area (2011)

Mumbai City 157 km2

Mumbai Suburban 446 km2

MMR 4,355 km2

Per Capita Income (2010-2011) Rs 1,41 lakh

GDDP at Constant Price in

2010-2011(2004-2005 Prices)

Rs 1,689,730 million

Table 8 - Socio economic facts, Mumbai

56

The infrastructure of transport in Mumbai has to appear to the rising demand.

Mumbai has 16.4 million houses i.e., twice as many people as those in New York city.

Mumbai is the most populated city of India and estimated about 12.4 million people.

Mumbai account for slightly more than 6.16% of Indian economy contributing 10% of

factory employment, 30% of income and 40% of foreign trade like most of the

metropolitan cities. Mumbai has a large influx of people from rural area looking for

employment.

The infrastructure of transport in Mumbai has to appear to the rising demand. Mumbai

has 16.4 million houses ie, twice as many people as those in New York city.

Roads

Eastern Freeway: It links P.D Mello road in south Mumbai to the eastern express highway

(EEH) at Ghatkopar which 16.8 km is about long and among 13.59 km stretch of the

freeway comprising two of three segment are operational and the rest is to be completed.

Figure 18 - Mumbai Road map

57

Coastal Road (West): The coast road is along the western coast from Narima point to

Malad 35 km long with inter changes at 18 locations connecting major roads. It also

connects both western and southern Mumbai.

Railways

Metro Rail: The metro rail system is 146 km length. It goes through the greater Mumbai

region from north to south and connects the airport and CBD which is located on the

southern part of the island.

Figure 19 - Railway network map of Mumbai

Mono Rail: Mumbai mono rail is 19.54 km and has 17 stations between Chempur and

Walada depot.

Western Railway: It connects the corridor from Avalmaidan to Virar.

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6.2.2 Surat

Surat is one of the major cities and the 8th largest city of India. It has the largest sea

port and it is now a center for diamond industry. The city is located 284 km South of the

Gujarat’s capital Gandhinagar, 265 km South of Ahmedabad and 289 km North of

Mumbai. It is one of the most fast-growing cities (GDP 11.5% over the last 7 years) and it

is known as the first smart IT Indian city. The city has 2.97 million internet users which

is 65% of total population.

Surat railway was built in 1860. The railway connects 245 bus routes linking major

localities. Surat international airport located in Magalala is 11 km South-West of Surat.

Apart from main city Surat airport also enters to narrow localities of South Gujarat.

Figure 20 – Mumbai socio-economic and transport scenarios

59

Population Concentration: The current population density varies from 10,400/sq.km to

53,000/sq.km and it is expected to vary between 34,000 and 50,000/sq.km in the coming

2 years.

Transport Systems: Most of the people travel across the region through road. Due to this,

these region faces traffic problem like congestion, air pollution and noise pollution.

The road network of Surat city is 372 km in 1976 to 644 km in 1990 showing an increase

rate of 18kms per annum.

The 3 existing railway stations in the city having 36 pairs of passenger trains in

total of 72 trains in both directions.

Figure 21 - Transport network of Surat

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6.2.3 Vadodara

It is the one of the largest cities in Gujarat as compared to Ahmedabad and Surat

with population 1.67 million people. Vadodara is the city with many large-scale

industries like India Oil Cooperation, IPCL, GACL, and many other major government

and private authority large scale industries have been setup. Over 35% of India’s power

transmission and distribution equipment manufacture industries are in this city. Many

other developing projects for IT and stock exchange are in progress.

Transport System in Vadodara

Vadodara has major rail and road network connecting with Delhi and Mumbai

with Ahmedabad. The transportation activities in Vadodara through air, rail and road

are discussed in the following.

Air

Vadodara airport is in North East of the city. It is the second green airport in India. It

has connection flights from major cities like Mumbai, New Delhi, Hyderabad, Chennai,

Kolkata and Bangalore.

Figure 22 - Vadodara rail network

61

Figure 24 Vadodara socio-economic facts

62

Railway

Vadodara railway is one of the oldest railways in India. The 10 major railways

stations in Vadodara are Pratapnagar, Vishwanitri, Makarapa, Karajan, Miygan, Itola,

Varnama, Bijwa, Ranoli, Nandesar. It now belongs to the Western railway zone of Indian

railway main line. It is the busiest railway in Gujarat with 358 trains passing each day.

Major long route trains like Rajadhani, Shabari, Durando and other Mail/ express trains

passes through these areas.

Road

Vadodara road connects Delhi and Gandhinagar with Ahmadabad to Surat which

passes through Mumbai by National Highway. Many road extension projects of National

Highway passing through Vadodara is been taking place.

There are over one hundred buses in Vadodara which is having a seat capacity of

33 to 50 persons. The people travelling through public and private transportation through

this road is facing many problems due congestion in peak time hours.

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6.2.4 Ahmedabad

Ahmedabad is sixth largest metropolitan city in India with a population of 68

million people. Ahmedabad is the fastest growing city in India and is listed as the 3rd

fastest growing city in the world after the Chine’s cities. The GDP of Ahmedabad is US

$ 64 billion in the year of 2014. The city is known for its cotton textiles, gem stones and

jewelries, the industries like automobile industry, chemical industry are growing in a

faster rate.

Figure 25 Ahmedabad socio-economic facts

Transport

Ahmedabad is one of six operating divisions in the Western Railway zone.

Railway lines connect the city to towns in Gujarat and major Indian cities. Ahmedabad

railway station, locally known as Kalupur station is the main terminus with 11 others.

The mass-transit metro system, MEGA for the cities of Ahmedabad and Gandhinagar is

under construction since March 2015.The North-South and East-West corridors are

expected to complete by 2019.

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National Highway 48 passes through Ahmedabad and connects with Delhi and

Mumbai. The National Highway 147 also links Ahmedabad to Gandhinagar. It is

connected to Vadodara through National Expressway 1, a 94 km (58 mi) long expressway

with two exits. This expressway is part of the Golden Quadrilateral project.

In 2001, Ahmedabad was ranked as the most polluted city in India, out of 85 cities,

by the Central Pollution Control Board. The Gujarat Pollution Control Board gave auto

rickshaw drivers an incentive of ₹10,000 to convert all 37,733 auto rickshaws in

Ahmedabad to cleaner burning compressed natural gas to reduce pollution. As a result,

in 2008, Ahmedabad was ranked as 50th most polluted city in India.

“Janmarg” is a bus rapid transit system in the city. It is operated by Ahmedabad

Janmarg Limited, a subsidiary of Ahmedabad Municipal Corporation and others.

Inaugurated in October 2009, the network expanded to 89 kilometers (55 mi) by

December 2015 with daily ridership of 1,32,000 passengers.

Sardar Vallabhbhai Patel International Airport, 15 km (9.3 mi) from the city Centre,

provides domestic and international flights. It is the busiest airport in Gujarat and the

eighth busiest in India with an average of 250 aircraft movements a day. Another airport,

The Dholera International Airport is proposed near Fedara (30 km from city). It will be

the largest airport in India with a total area of 7,500 hectares.

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6.3 HSR Project overview

India has undergone rapid economic growth in recent years, and along with this

growth has come a sharp rise in the volume of people and goods being transported in

the country. To meet this demand, the Ministry of Railways (MOR) and the Republic of

India, prepared the “Indian Railway Vision 2020” in December 2009. Seven routes have

been chosen as candidates for the High-Speed Railway (HSR). MOR and Republic of

India designates the line between Mumbai and Ahmedabad (approximately 500 kms as

the first HSR section to be constructed.

The region targeted by the study is a corridor having a length of approximately

500 kms that links Mumbai which is located in the state of Maharashtra in western India

and Gujarat, which form the target region of the study as provided in the image below.

Figure 26 Mumbai-Ahmedabad HSR alignment

The study area extends two states and two union territories in western India,

namely Maharashtra state, Gujarat state, Dadra and Nagar Haveli and Daman and Diu.

For HSR that operates at the maximum speed of 250–350 km/h, the vision plans to

implement projects by 2020. Furthermore, it will also make plans for multiple routes to

connect the commercial centers, tourist spots, pilgrimage destinations, and so on. Overall

66

cost of the construction is estimated to be Rs. 490-546 billion. And that of Rolling stock is

Rs. 67.83 billion.

Because the high-speed trains will enter the conventional line stations, the track

gauge and car width of the high-speed trains will be the same as the trains operate on the

conventional lines. ERTMS level 2 will be used as signaling standard and the rolling stock

will be the EMU, which is the mainstream of high-speed railway today. The feeding

method will use the AC 2*25kV system, which is standard for high-speed railway around

the world.

6.3.1 Basic characteristics

The construction method and operation method summarized in the ‘Characteristics

of section” in the above image are the important items in the selection of technical

specification in the pre-feasibility study by the French consultants. The main

characteristics are as follows:

• Because the high-speed trains will enter the conventional line stations, the track

gauge and car width of the high-speed trains will be the same as the trains operate

on the conventional lines.

• The signaling and telecommunication system ERTMS Level 2, which is the

interoperability standard in Europe, is selected.

• The rolling stock will be the EMU, which is the mainstream of high-speed railway

today.

• The feeding method will use the AC 2x25kV system, which is the standard for

high-speed railway in the world.

• The track will be ballast-less to enable operation at 350 km/h in the future.

Although it will mainly be an HSR line, the alignment is designed assuming entry into

conventional line stations, thus the same 1,676 mm gauge as the conventional lines will

be used. The plan is to cross Thane Creek by bridge. From a natural environment point

of view, because the surrounding area of Thane creek is designed as the Sanjay Gandhi

national park, it is subject to strict development regulations. As for crossing the Thane

creek SU1 route which will cross it at the downstream was recommended. However, the

construction will be affected because it will interfere with some of the Sanjay Gandhi

67

National park. The bridge of the SU2 route, which will cross the Thane creek at the

upstream, will also interfere with the Sanjay Gandhi national park. Moreover, since it is

planed that the route will pass through the eastern side of the Sanjay Gandhi sanctuary

north of Thane, it will interfere with part of the sanctuary thus the development

regulations are expected to remain a problem.

Because the plan is made for the Pune- Mumbai – Ahmedabad section, the alignment

near Navi Mumbai is designed in a delta shape to split into the Mumbai, Ahmedabad,

and Pune directions.

The breadth of the formation level is 13.6 m, which is wider than the plan which our

study team recommends. As a result, the required dimensions of the land and structures

are bigger. The long tunnels comply with the tunnel safety standards of European

specifications. The single-track tunnels will be constructed in parallel, with connection to

each other at an interval of 500 m as an evacuation route.

Overview of Project

Section Mumbai-Ahmedabad

Gauge 1676 mm

Civil engineering structures Length: approximately 504 kms

Track structure Ballast-less Fastened tracks

Signalling system ERTMS Level 2

GSM-R

Overhead catenary line Simple catenary system

Telecommunications GSM-R

Fare collection Use conventional method because the card system

is still in development

Train operation 80 trains/day (one-direction)

Rolling stocks E5 Series Shinkansen

Train length approximately 200 m

Alignment Construction standard for the design maximum

speed of 350 km/h (maximum curve radius 6425

m)

Financial and economic analysis Operating cost Rs. 2.05 billion

Maintenance cost: rolling stock Rs. 1.45 billion,

Infrastructure Rs. 2.54 billion Table 9 – Project overview, Mumbai-Ahmedabad HSR

Rolling Stock

EMU is the mainstream train set use in latest HSR which will also be used in this

project. The maximum speed is 350 kms/h, which is the feasible speed stated in the rolling

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stock specification, rather than the actual operating speed. It uses 1676 mm gauge

considering operation through conventional lines. Each bogie has 5 seats per row, car

width is 3265 mm, 8 cars per train set with the capacity of 600 people.

Electric power

The feeding system will be 2*25kV, the so-called Auto Transformer. It is becoming

standard feeding system of high-speed railways in the world. For the receiving system,

the receiving of a single-phase from the power company’s three-phase extra high voltage

transmission lines (225kV) is used.

Signaling and telecommunication unit

The ERTMS level 2 signaling system is used for the project used by European HSR

systems. ERTMS is developed to standardize the train protection systems so that trains

in Europe can operate interchangeably in all its countries.

Earthquake detection function

In HSR, it is important to stop the trains as soon as possible wen there is a disaster

of the danger of a disaster in order to prevent major accidents. The train will

automatically stop when the earthquake exceeds 65 MG.

As a result of the development of power electronics technology, the AC motor

driving system controlled by VVVF inverter is now used in wide ranges. In the case of

EMU type high-speed rolling stock, AGV trains use AC synchronous motors and other

trains AC induction motors. Induction motors are more advantageous in that they feature

a simple structure.

A train set of EMU type high speed railways is composed of plural traction units,

each having a transformer, converter-inverter and traction motor. Attention shall duly be

paid on to the traction unit to ensure environment-compatible propulsion performance,

guarantee redundancy against component failure.

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6.3.2 Stations

A station for the region from an extensive point of view has to be connected to

the regional transport mode such as Metro, BRT, taxi, buses and private vehicle and

also existing railway stations in several points to supply a connection for wide spread

HSR users. Roads, parking areas and station facilities for passengers will be designed to

handle large number of passengers with safety and with convenience.

Si. No Station name Distance

1 Mumbai 0 k 000

2 Thane 27 k 950

3 Virar 65 k 170

4 Boisar 104 k 260

5 Vapi 167 k 940

6 Bilimora 216 k 580

7 Surat 264 k 580

8 Bharuch 323 k 110

9 Vadodara 397 k 060

10 Anand/Nadiad 447 k 380

11 Ahmedabad 500 k 190

12 Sabarmati 505 k 750

Table 10 List of stations, Mumbai-Ahmedabad HSR

Out of the 12 stations, 3 stations have connectivity to Metro lines (Mumbai,

Ahmadabad and Sabarmati). All the stations have bus connectivity. Moreover 4 stations

have conventional rail connectivity which are Mumbai, Thane, Ahmadabad and

Sabarmati.

Structure types for elevated stations are categorized into two types based on the

platform type of each station. There are Island platform with 2 platforms and 4 lines

which has a RC rigid Frame, Separate platform with 2 platforms and 5 lines with an

integrated type of structure. Stations with this type of structure are, Thane, Boisar, Surat,

Bharuch, Vadodara, Ahmedabad, Sabarmati. Separate platform with 2 platforms with 4

lines has either rigid frame or hybrid type structure. Stations with this type of structure

are, Virar, Vapi, Bilomora, Anand/Nadiad.

70

6.3.3 Train operation plans

Train operation plan give the idea about the conditions with which the trains should

run on the line. It acts as a guideline for the train operators.

The basic concepts of train operation plan are as follows:

• To set maximum operation speed at 320 km/h to shorten the travelling time.

(Maximum design speed for the future is 350 km/h)

• To adopt the average passengers load factor of 70% for setting operation

plan.

• To set 2 types stop-patterns of train: In view of diverse needs of passengers,

a variety of origin and destination and a need to shorten the travelling time,

two types (rapid and each stop train) should be planned

• To separate operation time zone and maintenance time zone.

➢ Train operation time zone: 6:00-24:00 (0:00)

➢ Maintenance service time zone: 0:00-6:00

Two types of train planned are rapid train and each stop train. Rapid train will only

stop at major stations and each stop train will stop at every station. As the stations

where rapid train shall stop, Surat, Vadodara and Ahmadabad stations are proposed

while considering the fact that the number of passengers is overwhelming large

between Mumbai and Ahmedabad, between Mumbai and Surat and between Mumbai

and Vadodara.

Si. No Station name Distance Rapid train Each stop train

1 Mumbai 0 k 000 ● ●

2 Thane 27 k 950 ●

3 Virar 65 k 170 ●

4 Boisar 104 k 260 ●

5 Vapi 167 k 940 ●

6 Bilimora 216 k 580 ●

7 Surat 264 k 580 ● ●

8 Bharuch 323 k 110 ●

9 Vadodara 397 k 060 ● ●

10 Anand/Nadiad 447 k 380 ●

11 Ahmedabad 500 k 190 ● ●

12 Sabarmati 505 k 750 ● ● Table 11 – Stop pattern, Mumbai-Ahmedabad HSR

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6.4 Accessibility assessment

6.4.1 Calculation and evaluation of indicators

The indicators identified through the benchmarking exercise are introduced in

the section 5.2. In order to analyze the regional accessibility changes all the identified

indicators should be calculated using the pilot project data stated along the chapter 6.

The computation of those indicators using Mumbai-Ahmedabad HSR project details

and operational data is discussed in the following sections. The results of computation

using Excel solvers and corresponding data illustration using charts and graphs are also

included.

6.4.2 Weighted average travel times (location indicator)

The location accessibility indicator for the cities through which the HS rail line

passes is listed in the Table 12. The mass of the agglomerations is used as weight to value

the importance of minimal-time routes.

Table 12 Location indicator, Mumbai-Ahmedabad HSR

Location accessibility indicator

CITIES

scenarios differences

without HSR (min) with HSR (min) Absolute %

Mumbai 119 50 69 58

Thane 127 51 76 60

Virar 145 54 90 63

Boisar 169 58 111 66

Vapi 194 63 131 67

Bilimora 212 68 145 68

Surat 235 73 162 69

Bharuch 281 84 198 70

Vadodara 276 96 180 65

Anand/Nadiad 341 108 234 68

Ahmedabad 391 120 272 69

72

Figure 27 Absolute change in Weighted average travel time, Mumbai-Ahmedabad HSR

The new line will bring reduction of 151 minutes of average travel time ie, about

65% in the average travel time between the selected urban agglomeration. As the study

only covers the reduction of travel time of cities which are directly connected by the HSR

line, the city shows highest reduction in absolute travel time is Ahmedabad, with 272

minutes difference in new HSR line i.e., 69 % of the average travel time. In fact, the city

with highest benefit is Bharuch (70%). Bharuch shows a reduction of 198 minutes and the

city’s location in between two largest populations Mumbai and Ahmedabad influence on

this scenario. As explained, the location indicator does not emphasis on short distances,

along the line of HSR, cities such as Vapi, Bilimora, Surat and Bharuch show marginal

improvements than the cities in vicinity to the large agglomeration since like Mumbai or

Ahmedabad

The trend also shows more benefit to the cities with comparatively under

developed transport system in comparing with metros like Mumbai or Ahmedabad by

introducing a new high-speed rail network.

73

6.4.3 Economic potential

The economic potential value is calculated for all the cities in the study area, it

shows an average of 45 % rise in economic potential, i.e., 8,096 rises in the absolute value.

The average change in the economic potential is less than the rise shown is the previous

indicator, weighted average travel time (69 %).

Economic Potential

Cities

scenarios Difference

Without HSR With HSR Absolute %

Mumbai 77,363 101,522 24,159 31

Thane 455,195 631,270 176,075 39

Virar 217,995 328,498 110,503 51

Boisar 205,517 300,965 95,448 46

Vapi 156,139 228,875 72,736 47

Bilimora 171,542 260,544 89,001 52

Surat 100,059 141,899 41,841 42

Bharuch 231,571 338,690 107,120 46

Vadodara 112,989 170,513 57,525 51

Anand/Nadiad 176,863 264,198 87,336 49

Ahmedabad 63,040 92,040 29,000 46 Table 13 - Economic potential, Mumbai-Ahmedabad HSR

0

100000

200000

300000

400000

500000

600000

700000

Eco

no

mic

Po

ten

tial

Cities

Economic Potential

scenarios Without HSR scenarios With HSR

Figure 28 Change in Economic potential value, Mumbai-Ahmedabad HSR

74

Figure 29 - Heat map showing Average Economical potential along the HS Rail line (scenario without HSR)

The city with highest improvement in economic potential is Bilimora of 52% with

new line, simultaneously Virar and Vadodara. As mentioned, the potential indicator is a

gravity-based model and the values of cities near to the largely populated also reflect this

trend. The intermediate cities near to Ahmedabad and Mumbai such as Virar, Bilimora

and Vadodara show comparatively higher values. The self-potential of the Mumbai,

Thane and Ahmedabad influence the economic potential values of the cities. However,

the intermediate cities show the highest improvement economic potential, and this will

reflect the regional economic development.

75

Figure 30 - Heat map showing Average Economic potential along the HS Rail line (scenario with HSR)

Comparing the heat map indicating economic potential change to the difference

in weighted average travel time, the intermediate cities in vicinity to the bigger cities like

Mumbai and Ahmedabad are showing more improvements than the cities in far. In

general, the higher accessibility values are concentrated in the urban agglomerations

around the mega cities, as HSR lines allow them to reach the major cities with a shorter

travel time.

76

6.4.4 Daily accessibility indicators

In daily accessibility indicator the travel time limit should be determined first.

Instead of embracing European scenario, this study adapted Chinese experiences on

fixing travel time limits. The cut of limit in this study is set of 2 hour and by considering

the people’s willingness to travel and current transport scenarios of the region. With the

building of the new line the average accessible population with in the 2 hours travel time

limit for the selected urban agglomeration shows a rise of 5 million. This level of

improvements doubtfully high for a project but when accounting the fact that the

Mumbai-Ahmedabad HS rail connects one of the largest populations in the world makes

the values justifiable.

Daily accessibility indicator

cities

Scenarios Difference

Without HSR With HSR Absolute %

Mumbai 26,119,320 34,008,348 7,889,028 30

Thane 27,743,731 46,620,280 18,876,548 68

Virar 4,001,238 6,715,554 2,714,316 68

Boisar 4,281,086 6,936,055 2,654,969 62

Vapi 6,093,138 9,607,820 3,514,682 58

Bilimora 6,311,277 9,607,820 3,296,543 52

Surat 8,421,142 12,607,820 4,186,678 50

Bharuch 8,500,445 12,607,820 4,107,375 48

Vadodara 15,703,560 20,607,820 4,904,259 31

Anand/Nadiad 9,936,931 15,880,069 5,943,138 60

Ahmedabad 9,718,792 14,483,408 4,764,616 49 Table 14 Daily accessibility indicator, Mumbai-Ahmedabad HSR

Figure 31 Change in daily accessibility indicator, Mumbai-Ahmedabad HSR

0

20000000

40000000

60000000

80000000

Nu

mb

er o

f P

eop

le (

in t

rave

l tim

e lim

it)

Daily accessibility indicator

Scenarios Without HSR Scenarios With HSR

77

Figure 32 Heat map showing Daily Accessibility Indicator along the HS Rail line (scenario without HSR)

The percentage of rise in the accessible population in the major cities is showing

less rise in comparing with the intermediate cities. This is because of the large population

concentration in the cities with already developed accessible transportation network. In

the pilot project, Mumbai and Ahmedabad is showing this trend and with a rise of less

than 40 % rise in the number of accessible populations by the new line. On the other hand,

the intermediate cities such as Vapi, Bilimora, Surat, Bharuch shows potential rise of more

than 3 times ie, the number of people can reach these cities to carry out their purposes

and return in the same day is increased from half million to more than 3 million as a

reason of the project. The result also should interpret with the fact that these intermediate

cities comes under the 2 hours travelling limit of both Mumbai and Ahmedabad.

78

Figure 33 - Heat map showing Daily Accessibility Indicator along the HS Rail line (scenario with HSR)

In summary, the daily accessibility indicators forecast the economic boost in the

cities like Boisar, Billimore and Surat than Mumbai and Ahmedabad through

introduction of the new line. As it is already stated, this indicator provides an idea about

the numbers possible business contacts and market potentials like tourism, it is evident

that the new high-speed rail line will boost the regional economic growth and balance

the regional accessibility.

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6.4.5 Economic Accessibility

The correlation of economic indicator and accessibility change is already discussed

in the previous chapters. It is important to understand the influence of economic indicator

in accessibility improvement. So, the influence of economic indicator is analyzed in two

methods. One is cross country study. In cross country analysis, it accounts the financial

status of the users and their willingness to pay in different countries already

implemented and data available. GDP per capita of these countries compared with

India’s GDP per capita. And unit fare of each country is compared for the year 2014 (as

the data availability limited to the project announced in 2014) and for a projected price of

the year of opening. Secondly, fare level of other modes, compare air fare and rail fare

with HSR fare.

Cross Country fare Comparison : Figure 34 shows the fare for High Speed Railway for

500km in INR by country. As shown in the figure, the fare for the case of 1.5 times as

much as the fare for railway in 1A class in India is nearly equal to the fare in China.

The amount that an individual is willing to sacrifice to procure the transportation

service, highly depends on the income level of passengers. Following figure shows the

GDP per capita as of 2012 in USD at current price. The GDP (nominal) per capita in India

is approximately USD,500 in 2012. Comparing the countries which have the HSR, the

Figure 34 - Cross country comparison, Mumbai-Ahmedabad HSR

80

GDP per capita in India as of 2012 is low. For instance, the GDP per capita in France is 28

times of the GDP per capita in India but the unit price is only four times higher. Even if

it is assumed that the GDP will increase at 5 to 7 percent, the GDP per capita in India in

2023, the year of opening HSR, is USD 4,5801. Considering the fact, it is assumed that the

travelers in India regard the cost as important more than travel time comparing with the

developed countries.

Figure 35 - Cross country comparison (source: data elaboration from JICA Report)

As shown in Figure 35, the unit fare is mostly high in the country with high GDP

per capita. As GDP per capita indicates the financial performance of the country and

thereby the capability to afford the service. Thus, if India aims for the service level of

China or Russia for the time being, it is recommended that the unit fare level for HSR

should be range of 0.08 – 0.14 USD (Rs. 4.72 – 8.85) per kilometer, same as China or

Russia as of 2012.

Fare Level for Other Transportation Modes

Comparing the service level of HSR with other transport modes, four alternatives

fare for HSR is accounted in this study, namely 1) average fare of 2AC class and 3AC

class 2) same fare level as 1AC class of existing railway, 3) 1.5 times of 1AC class fare,

and 4) 2.0 times of 1AC class fare.

0

20,000

40,000

60,000

1,501 4,508 6,07110,52714,30220,33622,589

28,67033,11539,16141,22341,86643,61546,01146,707

GD

P p

er

cap

ita

Countries

81

Figure 36 - Fare comparison by mode (source: data elaboration from JICA Report)

The above chart shows the comparison of fare with other modes. It is clearly

evident that the HSR mode is far cheaper than the air fare and comparatively higher than

rail fare. When we add the comfort, time and safety HSR gains more edges than other

modes. Even though HSR is costly compared to bus and low-class fare of rail, it still holds

as a factor to cause a major mode shift to a certain category of people. Those categories of

people who currently affords the higher class of conventional rail and a major share of

air transport in the region. Thus, the fare level directly indicates the affordability and

thereby improving the accessibility such category of the Mumbai – Ahmedabad region.

0 500 1000 1500 2000 2500 3000 3500

India (Rail Avg. 2A&3A Case)

India (Rail 1A*1.0 Case)

India (Rail 1A*1.5 Case)

India (Rail 1A*2.0 Case)

Rail (SL)

RAil (3AC)

Rail (1AC)

Bus (A/C)

Air

Fare for 500 km (INR)

FARE COMPARISONBy mode

82

Chapter 7

Lessons learned from a comparative analysis

7.1 Summary of the pilot study.

In this pilot study, a set of identified indicators have been used to analyze the

regional accessibility from Mumbai-Ahmedabad HS rail project. This specific project is

adequate to the definition of HS rail transport system in its technical and operational

features, and thereby initiates the benchmarking exercise.

Four indicators identified from international experiences are used in this study,

such as Location indicator, Economic potential, Daily accessibility indicator and

Economic indicator. Except economic indicator, other three indicators give direct

measure of accessibility improvements, as in listed in Table . Alternately, economic

indicator provides a comparative analysis with competent modes and international

scenarios. Each indicator is evaluated separately on chapter 6.4.

Indicator Improvements

Absolute %

Location indicator 151 minutes 65 %

Economic potential 8096 EP value 45 %

Daily accessibility indicator 5713832 inhabitants 52 %

Table 11 – summary of the pilot study, Mumbai-Ahmedabad HSR

The highest average improvement in accessibility for the total group of the urban

agglomeration in study area is recorded for location indicator. Correspondingly, both

economic potential and daily accessibility indicators show improvement in accessibility.

The economic advantages with competent modes of transport are evident and well-

illustrated through economic accessibility indicator. It is evident that the effects of the

new line on accessibility will not be limited to the major metropolitan regions such as

Mumbai and Ahmedabad, but also in other areas of the regions like Virar, Surat and

Vadodara, through which the HSR passes. On the other hand, the accessibility impact of

the new HSR line will have an asymmetrical nature, since the large metropolitan cities in

the both ends of the line with higher weight of agglomeration than the other cities in the

study area.

83

In summary, the identified indicators explicitly state the accessibility

improvement achieved. Although, the study has limitations on an in-depth research of

the transport situation in pilot cities, this simple exercise has already asserted the

effectiveness of selected indicators. In addition, while evaluating, an indicator should not

be analysed in isolation. Understanding the interaction between the indicators will

provide a more meaningful and complete picture of the transport systems under study.

The study also demonstrated that it is difficult to obtain consistent data from all

participants but with the use of IT enabled tools and GIS tools facilitate this issue up to

certain level.

84

7.2 Comparative analysis with Madrid-Barcelona HSR ex-ante/ex-post

evidences.

Comparison to the similar experience provides better understanding of regional

accessibility improvement through HSR. Here, Madrid-Barcelona HSR evidence can be

analyzed in comparing to the case study. The ex-ante study already explained in section

4.1 uses the similar indicators of Mumbai-Ahmedabad case study. Besides, Madrid-

Barcelona HSR allows the possibility of ex-post analysis and data availability for duration

of 10 years instead of other relatively new HSR networks

An ex-ante analysis outlined in the section 4.1 explicitly states the accessibility

improvement with other modes. As the ex-ante term means, which gives an expected

value before the event that is before the HSR replaces the traffic in the region.

The ex-ante analysis result of Madrid-Barcelona HSR is much less than the

Mumbai-Ahmedabad case study. This difference can be seen in every indicator under

study. The maximum improvement shown for weighted average travel is 22% in Madrid-

Barcelona HSR at Zaragoza, which is less than the average value of weighted average

travel time (69%) on Indian HSR. Similarly, the economic potential indicator also shows

a rise of 45% average value, while Zaragoza is 37% and Barcelona has only 16%. This

difference is evident in daily accessibility indicator also, though the travel time limit and

regional population are different. When, Mumbai-Ahmedabad HSR shows a rise of 5

million inhabitancies in ridership whereas, the Spain case study shows a rise of 1 million

(1.64%) in daily accessibility indicator.

Observing an ex-post evidence of Madrid-Barcelona HSR along with the

comparison of ex-ante studies of both projects gives better understanding of future

regional accessibility improvements by Mumbai-Ahmedabad HSR. The ex-post analysis

of Madrid-Barcelona HSR carried out between 2000 and 2010 by using the same

indicators such as weighted average travel time, Economic potential and daily

accessibility indicators.

On ex-post analysis improvement in weighted average travel time is 28% is higher

than the ex-ante study conducted. But no large difference is evident. Similarly, ex-ante

and ex-post values of Economic potentials of Madrid-Barcelona HSR are 45% and 47%

respectively. As expected, the ex-post result is higher, but no marginal difference can be

85

seen. Meanwhile, the daily accessibility indicator is showing difference of 1 million to 1.5

million between ex-post and ex-ante scenarios.

By summing up, all the indicators calculate in ex-ante and ex-post studies shows

better accessibility improvements with no marginal difference in values. It should be

noted that the ex-post evidences are higher that the calculated ex-ante values. Thus,

similar improvement can be expected to the Mumbai-Ahmedabad HSR and this ex-post

evidence support the exercise conducted.

86

7.3 Recommendations for adopting the selected indicators

The identification and implementation of accessibility indicators in the pilot study

also put forwards some suggestions in adopting the indicators. The prime notion is about

understanding the accessibility change. Though the indicators show accessibility

improvement in the calculation, the result is inconsistent without understanding of which

indicator used. Because, as mentioned earlier, indicators behave differently based on their

conceptualization. So, the study recommends intercepting the indicators as the proposed

set not in isolation.

Further, regarding the data used. Apart from the transport network data,

information about the population, GDP and other attractiveness of destination centers

are used. This case study recommended that the selection of such parameters (e.g. Mj -in

weighted average travel time) should be based on data availability and reliability. This

study included population indices because of the reliability of National Census data for

the case study. Academic researches or basic level previously studies can be used with

online GIS tools like NASA Cedac earth data or similar platform. For further researches

demanding a more detailed level of calculation only recommends expensive GIS surveys

Modifications to adapt to regional socio-economic scenarios are also considered.

The travel time limit used for calculating the daily accessibility indicators is based on the

regional peculiarities such as willingness to travel. In pilot study, this limit is set to higher

than European limit by considering the Asian countries such as China with similar

backgrounds. In preference, the study recommends a separate detailed surveying before

fixing such variables considering the depth researches and affordability.

87

Chapter 8

Conclusions and Recommendations

This thesis work has carried out an analysis on regional accessibility improvement

related to the project development of Mumbai- Ahmedabad HSR. This project is the first

HSR experience in India. Prior to exploring the main subject, an overview of international

HSR systems has been provided along with a critical description of the concept of

accessibility.

Subsequently, a methodology for analyzing the regional accessibility of the case

study has been developed. As the motive of this paper stressed, this research intended to

identify and critically discuss a set of accessibility indicators followed by analyzing the

best practice from international experience. The selected indicators are weighted average

travel time (location indicator), economic potential, daily accessibility indicator and

economic indicator. As the study focus on regional accessibility improvement the

accessibility evaluation also proceeds with detailing of socio-economic backgrounds of

each city in the study area.

Considering the conclusion on the analysis the regional accessibility improvement

is explicit. Simultaneously, the inference on each indicator is distinct as the four indicators

offer complementary information about accessibility, since they respond to different

conceptualization. The magnitude and distributions of regional accessibility

improvements are stated and compared for the selected accessibility indicators. The

results vary from indicators to indicators. Concentrated effects on economic potential

indicators and daily accessibility indicators, whereas dispersed effects on location

indicator and economic indicator aim attention at user’s affordability of the

infrastructure.

In summary, the selection of indicators must caution because different conclusions

could be achieved according to geographical scale and accessibility indicator selected.

The study indicates definite improvement in regional accessibility with certain

disparities. The analysis also justifies the selection of indicators by addressing both

economic oriented and infrastructure-oriented growth between the scenarios with or

without HSR. This analysis method and selected set of indicators are not restricted to

HSR, but focus was kept on HSR infrastructure.

88

8.1 Future research developments

The increasing focus by governments and international development institutions

in infrastructure-based investment requires initiatives targeting the accessibility

improvement. The benchmarking concept studied under this research could be a useful

tool to support this drive for results. The global reach of international financial

institutions allows effective dissemination of knowledge and would suggest that such a

benchmarking initiative should be initiated as part of their development work.

It is therefore recommended that a gradual full-scale development/

implementation of a simple benchmarking initiative for urban transport in transition and

developing countries be implemented. This implementation will typically involve

initiatives such as refining the definition of the core indicators to take account of the

complexity of HS rail transport; collecting the relevant data for targeted implementation;

and Establishing a cooperative mechanism for continuous data collection.

Transport system is changing its phase in fast pace and concurrently the

information technology. Thus, linking the IT enabled tools to different process of

benchmarking and its implementation can play major role the future work. The role or

scope of technologies can be foreseen as developing a web-based data sharing and

dissemination platform that includes data analysis; the scope of GIS based online tools to

collect trip data such as travel time and destination choices; possibility of real time data

set available for the self-driving automated cars and its data accuracy and the possible

advancement of transport system analysis software like ArcGIS and other transport

modelling software’s.

89

List of Acronyms

ACT Australian Capital Territory

AECOM AECOM Technology Cooperation

ANOVA Analysis of Variance

ATC Automatic Train Control

AV Alta Velocita

AVE The Alta Velocidad Española

BRT Bus rapid transit

CBD Central Business District

EEH Eastern Express Highway

EMU Electric multiple unit

ERTMS European Rail Traffic Management System

ETCS European Train Control System

ETR Elettro Treno Rapido

GACL Gujarat Alkalies and Chemicals Limited

GDP Gross Domestic Product

GIS Geographic Information System

HSL High-Speed Line

HSR High-Speed Railways

INR Indian rupee

IPCL Indian Petrochemicals Corporation Limited

JICA Japan International Cooperation Agency

KNSO Korea National Statistical Office

KTX Korea Train express

90

LZB Linienzugbeeinflussung (cab signalling and train protection system)

MOR Ministry of Railways

NASA National Aeronautics and Space Administration

NSW New South Wales

NTV Nuovo Trasporto Viaggiatori

QLD Queens lands

RENFE Spanish National Rail Network

SNCF Société Nationale des Chemins de Fer français (French National Railway)

TGV Train à Grande Vitesse

UIC International Union of Railways

USD United States Dollar

VIC Victoria, Australia

VVVF variable-voltage/variable-frequency

91

List of figures Figure 1- HSR network of Japan (source: Japan Stations website) -------------------------------------------------- 14

Figure 2 - Japan HSR performance ------------------------------------------------------------------------------------------ 15

Figure 3 - Italy HSR map ------------------------------------------------------------------------------------------------------- 16

Figure 4 - Major freccia High-speed line map ---------------------------------------------------------------------------- 18

Figure 5 - France HSR network ----------------------------------------------------------------------------------------------- 19

Figure 6 - Germany HSR map (source: Transport Journal) ------------------------------------------------------------ 20

Figure 7 - Spain Rail Network map ----------------------------------------------------------------------------------------- 23

Figure 8 - China HSR map ------------------------------------------------------------------------------------------------------ 24

Figure 9 - The European high-speed network in the study area: scenario 2005. -------------------------------- 32

Figure 10 - Weighted average travel time change in the study area, Spain --------------------------------------- 33

Figure 11 - Study area map, China ------------------------------------------------------------------------------------------ 36

Figure 12 - Seoul case study area -------------------------------------------------------------------------------------------- 39

Figure 13 - Test result, Seoul case study ----------------------------------------------------------------------------------- 41

Figure 14 - Accessibility change plotted on study area ---------------------------------------------------------------- 42

Figure 15 - Proposed Australian HSR layout ------------------------------------------------------------------------------ 44

Figure 16 - Mumbai-Ahmedabad HSR map ------------------------------------------------------------------------------- 53

Figure 17 - Population density in the project affected area ---------------------------------------------------------- 54

Figure 18 - Mumbai Road map ----------------------------------------------------------------------------------------------- 56

Figure 19 - Railway network map of Mumbai ---------------------------------------------------------------------------- 57

Figure 20 – Mumbai socio-economic and transport scenarios ------------------------------------------------------- 58

Figure 21 - Transport network of Surat ------------------------------------------------------------------------------------ 59

Figure 22 - Vadodara rail network ------------------------------------------------------------------------------------------- 60

Figure 23 - Mumbai socio-economic and transport scenarios ------------------------------------------------------- 60

Figure 24 - Vadodara socio-economic facts ------------------------------------------------------------------------------- 61

Figure 25 - Ahmedabad socio-economic facts --------------------------------------------------------------------------- 63

Figure 26 - Mumbai-Ahmedabad HSR alignment ------------------------------------------------------------------------ 65

Figure 27 - Absolute change in Weighted average travel time, Mumbai-Ahmedabad HSR ------------------- 72

Figure 28 - Change in Economic potential value, Mumbai-Ahmedabad HSR ------------------------------------- 73

Figure 29 - Heat map showing Average Economical potential along the HS Rail line -------------------------- 74

Figure 30 - Heat map showing Average Economic potential along the HS Rail line (scenario with HSR) -- 75

Figure 31 - Change in daily accessibility indicator, Mumbai-Ahmedabad HSR ----------------------------------- 76

Figure 32 - Heat map showing Daily Accessibility Indicator along the HS Rail line ------------------------------ 77

Figure 33 - Heat map showing Daily Accessibility Indicator along the HS Rail line (scenario with HSR) --- 78

Figure 34 - Cross country comparison, Mumbai-Ahmedabad HSR -------------------------------------------------- 79

Figure 35 - Cross country comparison (source: data elaboration from JICA Report) --------------------------- 80

Figure 36 - Fare comparison by mode (source: data elaboration from JICA Report) --------------------------- 81

92

List of tables

Table 1 Japan HSR lines ............................................................................................................................... 15

Table 2 - German HSR lines ......................................................................................................................... 21

Table 3 Spain HSR lines ............................................................................................................................... 22

Table 5 China HSR lines ............................................................................................................................... 25

Table 6 China HSR ridership data ............................................................................................................... 26

Table 7 Change in travel time (source: Gutierrez 2001) ............................................................................. 33

Table 8 Key findings, Seoul case study ........................................................................................................ 41

Table 9 Socio economic facts, Mumbai ...................................................................................................... 55

Table 10 Project overview, Mumbai-Ahmedabad HSR ............................................................................... 67

Table 11 List of stations, Mumbai-Ahmedabad HSR ................................................................................... 69

Table 12 Stop pattern, Mumbai-Ahmedabad HSR ...................................................................................... 70

Table 13 Location indicator, Mumbai-Ahmedabad HSR ............................................................................. 71

Table 14 Economic potential, Mumbai-Ahmedabad HSR ........................................................................... 73

Table 15 Daily accessibility indicator, Mumbai-Ahmedabad HSR .............................................................. 76

93

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