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VISSIM Local Model Validation Report
March Area Transport Study July 2019
1
Document Control
Job number: CS095258 Document ref: CS/095258-CAP-TPL-XX-RP-TP-0060
Revision Purpose description Originated Checked Reviewed Authorised Date
1.0 Draft Report AC / EW JRH TLD TLD 22.02.19
1.1 Draft Report update to
comments
EW TLD TLD TLD 08.05.19
2.0 Final Report EW TLD TLD TLD 24.07.2019
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Table of Contents
Executive Summary ................................................................................................................................................ 1
Background ........................................................................................................................................................................... 1
Data Collection ...................................................................................................................................................................... 1
Model Traffic Flows ............................................................................................................................................................... 2
Model Development ............................................................................................................................................................. 2
Model Calibration / Validation .............................................................................................................................................. 2
Calibration / Validation Results ............................................................................................................................................. 3
1. Introduction ................................................................................................................................................... 4
1.1. Background ............................................................................................................................................................. 4
1.2. Structure of Report ................................................................................................................................................. 5
2. Modelling Introduction .................................................................................................................................. 6
2.1. Study Area .............................................................................................................................................................. 6
2.2. Traffic Modelling .................................................................................................................................................... 7
2.3. VISSIM .................................................................................................................................................................... 7
3. Data Collection ............................................................................................................................................. 10
3.1. Introduction .......................................................................................................................................................... 10
3.2. Manual Traffic Counts (MCC) ............................................................................................................................... 10
3.3. Fully Classified Automatic Count Data (ATC) ........................................................................................................ 12
3.4. Queue Data .......................................................................................................................................................... 14
3.5. Satellite Navigation Data ...................................................................................................................................... 16
3.6. Car Park Surveys ................................................................................................................................................... 17
3.7. Site Visits .............................................................................................................................................................. 17
3.8. Bus Services .......................................................................................................................................................... 17
3.9. Signals ................................................................................................................................................................... 18
4. Model Traffic Flows...................................................................................................................................... 19
4.1. Introduction .......................................................................................................................................................... 19
4.2. Traffic Flow Profile and Peak Hour Identification ................................................................................................. 19
4.3. ATC Data ............................................................................................................................................................... 20
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4.4. Balanced Turning Movements .............................................................................................................................. 22
4.5. Pedestrian Movements ........................................................................................................................................ 23
5. Model Development .................................................................................................................................... 24
5.1. Software ............................................................................................................................................................... 24
5.2. Highway Network ................................................................................................................................................. 24
5.3. Vehicles Composition ........................................................................................................................................... 25
5.4. Vehicle Inputs ....................................................................................................................................................... 25
5.5. Vehicle Routes ...................................................................................................................................................... 25
5.6. Traffic Control ....................................................................................................................................................... 25
5.7. Public Transport ................................................................................................................................................... 26
5.8. Outputs ................................................................................................................................................................. 27
6. Model Calibration and Validation ................................................................................................................ 28
6.1. Introduction .......................................................................................................................................................... 28
6.2. Calibration process ............................................................................................................................................... 28
6.3. Validation Process ................................................................................................................................................ 29
6.4. Traffic Flows ......................................................................................................................................................... 29
6.5. Travel Times ......................................................................................................................................................... 30
7. Base Model Calibration / Validation Results ................................................................................................ 31
7.1. AM Peak ............................................................................................................................................................... 31
7.2. PM Peak ................................................................................................................................................................ 35
7.3. Summary .............................................................................................................................................................. 39
8. Summary ...................................................................................................................................................... 40
8.1. Background ........................................................................................................................................................... 40
8.2. Data Collection ..................................................................................................................................................... 40
8.3. Model Traffic Flows .............................................................................................................................................. 40
8.4. Model Development ............................................................................................................................................. 41
8.5. Model Calibration / Validation ............................................................................................................................. 41
8.6. Calibration / Validation Results ............................................................................................................................ 42
Appendices ........................................................................................................................................................... 43
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Appendix A – AM and PM Peak traffic flows ....................................................................................................................... 43
Appendix B – Junction output AM and PM Peak ................................................................................................................ 44
Appendix C – Travel Time maps .......................................................................................................................................... 45
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Tables
Table 2.1: March Modelled Junctions ........................................................................................................................................ 9
Table 3.1: March Classified Counts (MCC) ............................................................................................................................... 11
Table 3.2: Incident Log – Dates Excluded Within Satellite Navigation Data ............................................................................ 16
Table 3.3: Car Parks in March with Capacity and Restrictions ................................................................................................. 17
Table 3.4: Bus Routes in MATS VISSIM Area ............................................................................................................................ 18
Table 4.1: Cumulative Traffic Flows ......................................................................................................................................... 19
Table 4.2: A141 Survey Data Comparison ................................................................................................................................ 21
Table 4.3: High Street Survey Data Comparison ...................................................................................................................... 21
Table 4.4: B1099 Dartford Road Survey Data Comparison ...................................................................................................... 21
Table 4.5: Station Road Survey Data Comparison .................................................................................................................... 21
Table 7.1: Traffic Flow Calibration Results – AM Peak ............................................................................................................. 31
Table 7.2: AM Peak Queue Comparison .................................................................................................................................. 33
Table 7.3: AM Peak Travel Time Comparison (secs) ................................................................................................................ 34
Table 7.4: Traffic Flow Calibration Results – PM Peak ............................................................................................................. 36
Table 7.5: PM Peak Queue Comparison................................................................................................................................... 37
Table 7.6: PM Peak Travel Time Comparison (secs) ................................................................................................................. 38
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Figures
Figure 1.1: March Area Transport Study .................................................................................................................................... 4
Figure 2.1: March Modelling Study Area ................................................................................................................................... 6
Figure 2.2: March Microsimulation Model Area ........................................................................................................................ 8
Figure 3.1: Manual Classified Turning Counts .......................................................................................................................... 12
Figure 3.2: Automatic Traffic Counts (21st March 2018) ......................................................................................................... 13
Figure 5.1: March VISSIM Structure ......................................................................................................................................... 24
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Executive Summary
Background
In January 2018, the Cambridgeshire and Peterborough Combined Authority (CA), through Cambridgeshire
County Council (CCC) and Fenland District Council (FDC), agreed a draft brief for the March Area Transport Study
(MATS). In March 2018 Skanska / Capita issued a Stage 0 Inception Report that explained in detail the work
needed to undertake the Stage 1 MATS.
Following this report Skanska / Capita were commissioned to undertake Stage 1 of the Study, part of which
involves this 'Microsimulation Local Model Validation Report’. The figure below shows how the component parts
of the MATS study fit together. This report has been produced collaboratively by Skanska and Capita.
The MATS micro-simulation model area spans from B1101 Twenty Foot Road in the north, to the Mill Hill
roundabout in the south, the B1011 and B1099 St Peter’s Road to the east and A141 to the west.
Data Collection
The following data collection was undertaken during 2018:
• Manual Classified Count (MCC) data on Tuesday 27th March and Wednesday 28th March
• Four Automatic Traffic Count (ATC) sites were surveyed over a two-week period between
Wednesday 21st March and Tuesday 3rd April
• Queue length surveys were undertaken on Tuesday 27th March 2018 at 7 highway junctions
and 4 level crossing sites
• Satellite Navigation data for the March study area was collected between the 5th March and
28th March
• Car Park survey data was collected with the MCC data and surveyed on the 12th June
• Bus routes were collected from https://www.fenland.gov.uk/busandcoach
• Signal specifications for the signalised junctions were provided by CCC
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A site visit was undertaken on Tuesday 27th March 2018 (day of the survey) in the AM and PM Peak periods when
traffic conditions within the study area were observed.
Model Traffic Flows
The traffic flow profiles for the AM and PM peak period were calculated using the four ATC sites monitored
during the traffic surveys (A141, B1101 High Street, B1101 Station Road and B1099 Dartford Road), and the
corresponding turning counts (MCC data). The peak hours selected to model were 08:00 – 09:00 and 17:00 –
18:00. The ATC traffic data for each site was compared to the MCC traffic flows for the AM and PM peak periods,
to ensure that the survey day was representative of typical site conditions.
Within VISSIM, traffic flows need to be balanced. The survey data was utilised to produce a network of raw,
unbalanced turning movement flows in 15-minute intervals for vehicles. The unbalanced network was then
balanced between junctions. The ATC data was utilised to aid the balancing of the traffic flows. Pedestrian counts
across the pedestrian crossings in the town centre were surveyed using video footage from the MCC surveys.
Model Development
VISSIM version 10.00-04 (the most recent version at time of commission) has been used to construct and run
the model. The base road network for the existing conditions VISSIM model was constructed for both peaks
using Ordnance Survey background. The model is based on ‘static assignment’ throughout the network on an
origin and destination basis for each junction. Vehicle Inputs, Routes and Compositions were collated from the
balanced stick diagrams from the MCC data. The bus routes were coded separately into the model. Priority rules
were placed at all give-way locations throughout the network. The signalised junction was modelled using VisVap
and PCMOVA. The level crossings were also modelled using signalised operation.
Model Calibration / Validation
It is necessary to calibrate and validate the base model to confirm that the model is fit for purpose for evaluating
proposed improvement measures.
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A number of adjustments were carried out during the calibration process including:
• Driving Behaviour and Link Types
• Speeds – speed distributions and reduced speeds
• Priority Rules
• Signals
• Pedestrians
Although WebTAG (which is the Department for Transport’s guidance on appraising transport projects and
proposals) does not provide explicit guidance for validation of micro-simulation models, the overall principles
applied to strategic model validation have been followed. For turning flows, the GEH statistic has been used as
a measure for model validation and observed travel times have been compared to the modelled travel times.
The acceptance criteria of modelled journey times are within +/- 15 percent or 1 minute of surveyed journey
times for 85% of routes. Observed and Modelled queue lengths have also been compared.
Calibration / Validation Results
In summary, in the AM Peak
• All junction movements have a GEH of under 5
• There is generally a good match between observed and modelled queue lengths
• 85% of travel times are within the validation criteria.
In Summary, in the PM Peak
• All junction movements have a GEH of under 5
• There is generally a good match between observed and modelled queue lengths
• 88% of travel times are within the validation criteria.
Overall, taking into account all the validation data, the model is believed to be representative of observed
conditions in the AM and PM Peak and can be taken forward to be used for option testing.
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1. Introduction
1.1. Background
1.1.1. In January 2018, the Cambridgeshire and Peterborough Combined Authority (CA), through
Cambridgeshire County Council (CCC) and Fenland District Council (FDC), agreed a draft brief for the
March Area Transport Study (MATS) to develop a Stage 0 Audit and Scoping document (Inception
Report). The Brief set out the aims and the scope of the wider MATS project, explained the
expectation of the Inception Report (Stage 0) and provided context and background to the March
area. In March 2018 Skanska / Capita issued a Stage 0 Inception Report that explained in detail the
work needed to undertake the Stage 1 MATS.
1.1.2. Following this report Skanska / Capita were commissioned to undertake Stage 1 of the Study, part of
which involves this 'Microsimulation Local Model Validation Report’. Figure 1.1 shows how the
component parts of the MATS study fit together. This report has been produced collaboratively by
Skanska and Capita.
Figure 1.1: March Area Transport Study
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1.2. Structure of Report
1.2.1. This report has been structured as follows:
• Chapter 2 describes the Study Area
• Chapter 3 documents the data collection
• Chapter 4 details the model process
• Chapter 5 documents the model development
• Chapter 6 documents in detail the calibrations and validation of the model
• Chapter 7 explains the 2018 base model calibration and validation results
• Chapter 8 is a summary of the report
• Appendix A – AM and PM Peak traffic flows
• Appendix B – Junction output AM and PM Peak
• Appendix C – Travel Time maps
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2. Modelling Introduction
2.1. Study Area
2.1.1. The project is in the Fenland market town of March, Cambridgeshire. The March Area Transport Study
(MATS) area spans from B1101 Twenty Foot Road in the north, to the Mill Hill roundabout in the
south, the B1011 and B1099 St Peter’s Road to the east and A141 to the west. The area covers the
main roads in and out of March town centre. The study area can be seen in Figure 2.1.
Figure 2.1: March Modelling Study Area
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2.2. Traffic Modelling
2.2.1. Microsimulation software, VISSIM, has been used for the MATS project for modelling the corridor and
outline highway designs in more detail. VISSIM software is part of the PTV Vision Transport modelling
suite. It is a microscopic traffic flow simulation model based on car following and lane change logic.
VISSIM can analyse vehicular traffic including bus / tram, pedestrian and bicycle operations, under
constraints such as lane configuration, traffic composition, traffic signals, and bus / tram stops. VISSIM
does not follow the conventional link / node modelling system, but utilises a link / connector system
that enables complex highway geometry to be modelled. The link / connector system also permits
different traffic controls (signal, give way or stop) to be utilised anywhere in the model. VISSIM is also
capable of modelling vehicle actuation traffic control, utilising the Vehicle Actuated Programming
(VAP) module, as well as MOVA using the PCMOVA module from TRL. Therefore, it is an appropriate
tool for the evaluation of existing conditions and for testing scheme options within the March study
area.
2.2.2. VISSIM version 10.00-04 (the most recent version at the time of commission) has been used to
construct and run the model.
2.3. VISSIM
2.3.1. Figure 2.2 shows the extents of the VISSIM model.
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Figure 2.2: March Microsimulation Model Area
2.3.2. Table 2.1 shows all the junctions that have been included in the VISSIM model. The node numbers
used in the model have also been included.
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Table 2.1: March Modelled Junctions
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3. Data Collection
3.1. Introduction
3.1.1. For more detailed information on Data Collection undertaken for MATS please refer to the ‘Existing
Conditions and Data Collection Report’ dated December 2018.
3.2. Manual Traffic Counts (MCC)
3.2.1. MCCs were undertaken on Tuesday 27th and Wednesday 28th March 2018. These surveys recorded
vehicle turning movements at each surveyed junction in 15 minute intervals over a 12-hour period,
between 07:00 and 19:00 hours. Vehicle classifications captured within these surveys include Car,
Light Goods Vehicle (LGV), Other Goods Vehicle 1 (OGV 1), Other Goods Vehicle 2 (OGV 2), Bus (PSV),
Motorcycle (MC) and Pedal Cycle (PC).
3.2.2. Table 3.1 lists all the MCC sites that were surveyed on Tuesday 27th and Wednesday 28th March 2018
and Figure 3.1 shows the spatial distribution of the sites over the study area.
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Table 3.1: March Classified Counts (MCC)
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Figure 3.1: Manual Classified Turning Counts
3.3. Fully Classified Automatic Count Data (ATC)
3.3.1. Four ATC sites were surveyed over a two-week period between Wednesday 21st March and Tuesday
3rd April 2018. These dates cover the survey dates for the MCCs (Tuesday 17th and Wednesday 18th
March). The ATCs were used to identify the AM and PM peak hours for March and to determine
13
whether the MCC data is a representative sample. Figure 3.2 shows the location of ATC sites.
Figure 3.2: Automatic Traffic Counts (21st March 2018)
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3.3.2. ATC data collected was recorded in 15-minute intervals, broken down into direction and
classifications of speed (mean average and 85th percentile) for the vehicle types Car, Light Goods
Vehicle (LGV), Other Goods Vehicle 1 (OGV 1), Other Goods Vehicle 2 (OGV 2), Bus (PSV), Motorcycle
(MC) and Pedal Cycle (PC).
3.4. Queue Data
3.4.1. Queue length surveys were undertaken on Tuesday 27th March 2018 at 7 highway junctions and 4
level crossing sites. Data was recorded at 5-minute intervals for each approach to the junction and
every time a barrier interaction took place at the level crossings. The locations where queue length
data was collected are shown in Figure 3.3.
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Figure 3.3: Queue Length and Barrier Timing Survey Locations
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3.5. Satellite Navigation Data
3.5.1. Satellite Navigation data for the March study area was collected between the 5th March and 28th
March 2018. It should be noted that the dataset collected excludes weekends and bank holidays as
well as any other days when road closures occurred (A47 Thorney Toll, Guyhirn / Wisbech
Roundabout) or during severe weather conditions as shown in Table 3.2 below.
Table 3.2: Incident Log – Dates Excluded Within Satellite Navigation Data
Time periods collected included:
• Free Flow 00.00 – 05:00
• AM Shoulder 1 07:00 – 08:00
• AM Peak 08:00 – 09:00
• AM Shoulder 2 09:00 – 10:00
• Inter Peak 14:00 – 15:00
• PM Shoulder 16:00 – 17:00
• PM Peak 17:00 – 18:00
• Evening 18:00 – 19:00
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3.6. Car Park Surveys
3.6.1. Car park data was collected from count data as well as from interviews and a postcard survey. Data
was collected on the 12th June 2018, for the 12-hour period between 07:00 - 19:00. Car parks that
were surveyed are listed below in Table 3.3. Please note that Sites 5, 6, 8 and 9 represent
supermarket-owned car parks, Site 10 belongs to Network Rail (leased to Greater Anglia), whilst the
remaining sites are council owned car parks.
Table 3.3: Car Parks in March with Capacity and Restrictions
3.7. Site Visits
3.7.1. A site visit was undertaken on Tuesday 27th March 2018 (day of the MCC surveys) in the AM and PM
Peak periods when traffic conditions within the study area were observed.
3.8. Bus Services
3.8.1. The bus routes were collected from https://www.fenland.gov.uk/busandcoach and are shown below
in Table 3.4. The routes were confirmed with FDC.
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Table 3.4: Bus Routes in MATS VISSIM Area
3.9. Signals
3.9.1. CCC provided the signal specifications for the signalised junctions. There are three signalised junctions
within the network including:
• B1099 Dartford Road / B1101 Broad Street / B1101 Station Road / Robingoodfellow’s Lane
• B1101 The Causeway / B1101 High Street / B1099 St Peter’s Road
• A141 March Road / A605
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4. Model Traffic Flows.
4.1. Introduction
4.1.1. For more information on Model Traffic Flows please see the ‘Existing Conditions and Data Collection
Report’ dated December 2018.
4.2. Traffic Flow Profile and Peak Hour Identification
4.2.1. The traffic flow profiles for the AM and PM peak period were calculated using the four ATC sites
monitored during the traffic surveys (A141, B1101 High Street, B1101 Station Road and B1099
Dartford Road), and the corresponding turning counts (MCC data).
4.2.2. Table 4.1 shows the traffic flow profiles for both the AM and PM peak periods. Note that these are
the cumulative flows and therefore represent hourly flows, not just for the 15 minute periods listed.
The highlighted green box shows the highest cumulative flow.
Table 4.1: Cumulative Traffic Flows
4.2.3. Table 4.1 shows traffic flows are similar across the cumulative hours assessed, with peak hours
identified as 07:45 – 08:45 for the AM peak and 16:45 – 17:45 for the PM peak hour. The peak hours
selected to model are 08:00 – 09:00 and 17:00 – 18:00, for the following reasons:
• There are only minor differences between cumulative flows in each 15-minute period.
• The difference between 07:45 – 08:45 and 08:00 – 09:00 is less than 9 vehicles across all three
sites.
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• The peak is nearer to 08:00 – 09:00 in the Town Centre (the A141 site 184 adjusts the
cumulative hour total forwards marginally).
• The difference between 16:45 – 17:45 and 17:00 – 18:00 is negligible (16 vehicles).
• 08:00-09:00 and 17:00-18:00 peak hours are more consistent with other datasets, the strategic
SATURN model peak hours and other traffic assessments such as transport assessments, which
makes data comparison and analysis simpler.
4.3. ATC Data
4.3.1. The ATC traffic data for the two-week average for each site was compared to the MCC traffic flows
for the AM and PM peak periods, to ensure that the survey day was representative of typical site
conditions. A summary of this comparison is shown in Tables 4.2, 4.3 and 4.4 below.
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Table 4.2: A141 Survey Data Comparison
4.3.2. Table 4.2 shows traffic flows recorded along the A141 are similar for the ATC and MCC counts. A
greater difference is shown northbound during the AM peak and then southbound during the PM
peak hour.
Table 4.3: High Street Survey Data Comparison
4.3.3. Table 4.3 shows the PM peak hour recorded at High Street, has marginal differences between the ATC
and MCC data. In the AM peak hour, both northbound and southbound, the MCC is slightly higher
than the ATC. Despite differences shown, the MCC data count is higher and therefore will offer a more
robust analysis when utilised in the modelling process.
Table 4.4: B1099 Dartford Road Survey Data Comparison
4.3.4. Table 4.4 shows that the ATC data is slightly lower than the MCC data across all peaks and in both
directions for the B1099 Dartford Road. This difference however is consistently small (being no more
than 6%) and is likely due to queues forming across the ATC counting equipment and reducing its
effectiveness.
Table 4.5: Station Road Survey Data Comparison
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4.3.5. For the Station Road survey, Table 4.5 shows the ATC and MCC data are fairly balanced across all peak
hours, with a maximum difference shown of 26 vehicles.
4.4. Balanced Turning Movements
4.4.1. Within VISSIM, traffic flows need to be balanced so that within the network overall, the same amount
of traffic enters and exits the network. The survey data was utilised to produce a network of raw,
unbalanced turning movement flows in 15-minute intervals for vehicles. The unbalanced network was
then balanced between junctions. The ATC data was utilised to aid the balancing of the traffic flows.
4.4.2. The balanced traffic flows were undertaken for two separate vehicle classes. One for vehicle type Car,
LGV, OGV 1 and motorbike and another one for OGV2. This is so OGV2 vehicle type is routed correctly
around the network due to the weight limit restriction in the town centre over the river bridge.
4.4.3. ‘Sinks and Sources’ were added to aid balancing the flows where there were big differences in flow
between junctions (sink and sources are utilised to model entrances and exits for traffic to the model).
These were at the locations below:
• Russell Avenue / Norwood Road
• Market Place Car Park
• Dagless Way
4.4.4. The balanced traffic flows for the AM Peak and PM Peak period for the model network are shown in
Appendix A.
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4.5. Pedestrian Movements
4.5.1. Pedestrian counts across the pedestrian crossings in the town centre were surveyed using video
footage from the MCC surveys. The pedestrian crossings counted include:
• Wisbech Road – Signalised
• Dartford Road – Signalised
• Broad Street South – Signalised
• Market Place – Signalised
• Burrowmoor Road near City Road – Signalised
• The Causeway – Signalised
• Neale Wade Academy – Signalised
• High Street South – Zebra
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5. Model Development
5.1. Software
5.1.1. VISSIM version 10.00-04 (most recent version at the time of commission) has been used to construct
and run the model.
5.2. Highway Network
5.2.1. The base road network for the existing conditions VISSIM model was constructed for both peaks using
Ordnance Survey background. Figure 5.1 shows the VISSIM model network.
Figure 5.1: March VISSIM Structure
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5.3. Vehicles Composition
5.3.1. VISSIM models individual vehicles grouped into vehicle types and then by vehicle classes. Vehicle
classes for Car, LGV, OGV1, OGV2, Bus and Motorcycle were used within the model. The Car vehicle
class was split into small (75%) and large (25%) cars, based on past experience.
5.4. Vehicle Inputs
5.4.1. The vehicle input for the model is derived from the AM and PM peak balanced stick diagrams from
the MCC data. Inputs into the model have been entered in 15-minute segments.
5.4.2. Prior to the start of the peak the network is loaded with additional traffic to achieve a realistic model
output for the peak hour, called a warm-up period. A 30-minute warm-up period has been used for
this model.
5.5. Vehicle Routes
5.5.1. The model is based on ‘static assignment’ throughout the network on an origin and destination basis
for each junction. Static assignment is when vehicles are input directly and routes between origins
and destinations are determined manually by the user. The routes for the network are derived from
the balanced turning counts shown in Appendix A which were derived from the MCC data. Like the
inputs, the routes are based on 15-minute segments to profile the traffic throughout the peak hour.
The routes throughout the model have been coded in junction to junction.
5.6. Traffic Control
5.6.1. Priority rules were placed at all give-way locations throughout the network.
5.6.2. A number of junctions in the network are signal controlled by MOVA or Vehicle Actuated (VA) systems
including:
• B1101 Station Road \ B1099 Dartford Road \ Broad Street - VA
• B1101 High Street \ B1101 The Causeway \ B1099 St Peter’s Road - VA
• A141 Wisbech Road \ A141 March Road \ A605 Rings End. – MOVA
26
5.6.3. MOVA is a traffic control strategy that continually adjusts the green time required for each approach
by assessing the number of vehicles approaching the signals, whilst at the same time determining the
impact that queuing vehicles would have on the overall operation of the junction. The junctions
operating on MOVA have been coded into the model using TRL software add-on, PC MOVA 2. PC
MOVA uses the MOVA datasets for the junction to simulate in VISSIM how the MOVA dataset is
working on site.
5.6.4. The junctions operating on Vehicle Actuated (VA) signals have been set up using VISSIM's add-on
program VisVap, to code the signals as they operate on site with 'gap outs' and demand. Signal 'gap
out' is a type of actuated operation for a given phase, where the phase terminates due to a lack of
vehicle calls within a specific period of time.
5.6.5. Signalised pedestrian crossings were modelled using VisVap to code the ‘at demand’ crossings.
Therefore, the signals in the model will be called when there is pedestrian demand as per on-site
conditions.
5.6.6. The level crossings in the March VISSIM model were simulated using traffic signals. The signals were
coded to be on green when the barrier was up, and red when the barrier was closed. The barrier
close time and duration were collated from the survey data. The three level crossings in the model
include:
• Station Road Level Crossing
• Norwood Road Level Crossing
• Creek Road Level Crossing
5.6.7. Upwell Road Level Crossing was not included as it is not in the model network.
5.7. Public Transport
5.7.1. The bus routes were coded in the VISSIM model separately. To code when a bus would enter the
network, the nearest stop on the edge of the network was chosen for the start time of the service.
The up-to-date timetables and maps for most of the services in March can be found at
https://www.cambridgeshire.gov.uk/residents/travel-roads-and-parking/buses/bus-timetables/.
5.7.2. After discussion with FDC it was identified that some of the routes were different to those on the
Cambridgeshire website. Updated bus route maps were sent through on the 12th of September 2018.
5.7.3. The dwell times for all other bus stops within the network have been set to the default value of 20
seconds with a 5 second standard deviation, as observed dwell times were not available.
27
5.8. Outputs
5.8.1. The following outputs were collected from the VISSIM model including:
• Modelled Traffic Flows
• Modelled Queue Lengths
• Modelled Travel Times
28
6. Model Calibration and Validation
6.1. Introduction
6.1.1. It is necessary to calibrate and validate the base model to confirm that the model is fit for purpose
for the evaluation of proposed improvement measures. Calibration involves changing the model set-
up and behavioural characteristics to achieve a match between observed and modelled data. Model
validation assesses the accuracy of the model by comparing traffic data from the model with other
sources of traffic data that were not used in the model build process.
6.2. Calibration process
6.2.1. During calibration, the network has been checked and adjustments have been made to improve the
performance of the model, based on comparisons with observed data and the site visit.
6.2.2. The following adjustments set out in A-E below, were carried out during the calibration process:
A) Driving Behaviour and Link Types
• Urban motorised – has been used on most link types for the study area
• Footpaths have been coded in for pedestrian crossings
B) Speeds
• Throughout the network different speed distributions have been used and these have been
set according to the speed limits within the network.
• Within the network where there is a change in speed limit, desired speed decisions have been
used.
• Reduced Speed Areas are used to model an area where speed is reduced, for example a bend
or as vehicles are accelerating from a complete stop at a junction. Reduced speed areas were
applied to all turns throughout the network.
• Reduced Speeds have been used where there are speed bumps, road narrowing, traffic
calming and speed cameras throughout the model network.
• Reduced Speeds were also used to model areas in the model where parked cars (both legal
and illegal) slow traffic within the network.
• At signalised junctions, saturation flows (measure of the maximum rate of flow of traffic) can
be lower than at priority junctions, as vehicles can be slower to accelerate after they have
stopped at traffic lights. Reduced speed areas were also added to decrease saturation flows
at the signal stop-lines, to aid replicating observations on site.
29
C) Priority Rules
• Priority Rules were used throughout the model to replicate on site observations, including give
ways and yellow boxes.
D) Signals
• All signals have been run as per the specifications and MOVA datasets.
E) Pedestrians
• Video surveys were used to collate pedestrian numbers throughout the model. Where no data
was available for the pedestrian crossings, a default of 20 pedestrians per hour per direction
was used. These have been updated as per validation.
F) Random Seeds
• Due to the stochastic nature of VISSIM, the model was run for 20 random seeds as per TfL
guidance on micro-simulation. The manual states that "random fluctuations occur in the
results of the individual simulation runs. A more reliable assertion is only reached through
averaging the results of enough simulation runs with different random seeds".
E) Queue Lengths
• The observed and modelled queue lengths were compared for both peak periods and used as
part of the calibration process to ensure the profile was reasonable and the proportions of
queuing at the approaches surveyed was representative.
6.3. Validation Process
6.3.1. Although WebTAG does not provide explicit guidance for validation of micro-simulation models, the
overall principles applied to strategic model validation have been followed.
6.4. Traffic Flows
6.4.1. For turning flows, the GEH (named after Geoffrey E. Havers) statistic has been used as a measure of
model validation. GEH is often described as a 'goodness of fit' statistic, as it takes into account both
the absolute and relative difference between modelled and observed flows, with the target being a
GEH of < 5.
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6.4.2. The GEH statistic is defined as:
( )
12
2
122
VV
VVGEH
+
−=
where:
V1 = the observed flow; and
V2 = the modelled flow.
6.4.3. In summary, for validation, a GEH value of ≤5.0 is needed in at least 85% of cases.
6.5. Travel Times
6.5.1. The observed travel times have been compared to the modelled travel times for the March VISSIM
Study area. The WebTAG acceptance criteria of modelled journey times are within +/- 15 percent or
1 minute of surveyed journey times for 85% of routes. For validation, the travel times from the model
were collated for all vehicles except buses.
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7. Base Model Calibration / Validation Results
7.1. AM Peak
7.1.1. A summary of the overall traffic flow calibration results by overall total of all turning movements on
a junction basis for the base AM peak period model, is shown in Table 7.1.
7.1.2. Volume is the total flow into the junction, summed across all approach arms
Table 7.1: Traffic Flow Calibration Results – AM Peak
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7.1.3. Table 7.1 shows that all junctions have a GEH of under 5, therefore there is an excellent fit between
observed and modelled traffic flows. The full output by turning movement is in Appendix B.
7.1.4. A summary of the comparison between modelled and observed queue lengths for the base AM peak
period model is shown in Table 7.2.
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Table 7.2: AM Peak Queue Comparison
7.1.5. Table 7.2 shows there is generally a good match between observed and modelled queue lengths.
7.1.6. Also, in comparison to google maps typical traffic for 0800-0900, the queues in the model match well
with the locations that lower speeds are highlighted in the google maps network.
7.1.7. There are differences between the modelled and observed queue lengths however, which may be
due to:
• The maximum observed queue length recorded was the ‘reach extent’ of camera view;
therefore, the full extent of the queue has not been captured
• The observed queue lengths are taken every 5 minutes, with queue lengths at signalised
junctions generally recorded at the beginning of the green phase (when the queue is the
longest)
• Within VISSIM, queue lengths are recorded for every time step (a rate of 10 recordings per
second); therefore, queue lengths are recorded throughout the whole cycle time
7.1.8. Queue lengths in isolation are not therefore considered to be an appropriate measure for complete
validation.
7.1.9. A summary of the comparison between modelled and observed travel times for the base AM peak
period model for all vehicles excluding buses, is shown in Table 7.3. Maps of all the travel time routes
are shown in Appendix C
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Table 7.3: AM Peak Travel Time Comparison (secs)
35
7.1.10. Overall, Table 7.3 shows that in the AM peak, 85% of travel times are within the acceptance criteria
of modelled journey times (within +/- 15 percent of surveyed journey times). It should be noted that
the modelled travel times that do not meet the criteria are still close to the observed travel time.
7.2. PM Peak
7.2.1. A summary of the overall traffic flow calibration results by overall total of all turning movements on
a junction basis for the base PM peak period model, is shown in Table 7.4.
36
Table 7.4: Traffic Flow Calibration Results – PM Peak
7.2.2. Table 7.4 shows that all the junctions have a GEH of under 5. Therefore, there is an excellent fit
between observed and modelled traffic flows. The full output by turning movement is in Appendix B.
7.2.3. A summary of the comparison between modelled and observed queue lengths for the base AM peak
period model is shown in Table 7.5.
37
Table 7.5: PM Peak Queue Comparison
7.2.4. Table 7.5 shows there is generally a good match between observed and modelled queue lengths.
7.2.5. Also, in comparison to Google Maps typical traffic for 1700-1800, the queues in the model are in the
locations that lower speeds are highlighted in the Google Maps network.
7.2.6. A summary of the comparison between modelled and observed travel times for the base PM peak
period model for all vehicles excluding buses, is shown in Table 7.6.
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Table 7.6: PM Peak Travel Time Comparison (secs)
39
7.2.7. Overall Table 7.6 shows in the AM peak, 88% of travel times are within the acceptance criteria of
modelled journey times (within +/- 15 percent of surveyed journey times). It should be noted that the
modelled travel times that do not meet the criteria are still close to the observed travel time.
7.3. Summary
7.3.1. Overall, taking into account all the validation data, the model is believed to be representative in the
AM and PM Peak of observed conditions and can be taken forward to be used for option testing.
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8. Summary
8.1. Background
8.1.1. As part of the March Area Transport Study (MATS) Skanska / Capita were commissioned to build a
VISSIM microsimulation model and complete a ‘Microsimulation Local Model Validation Report’. The
report has been produced collaboratively by Skanska and Capita.
8.1.2. The March Area Transport Study (MATS) model area spans from B1101 Twenty Foot Road in the
north, to the Mill Hill roundabout in the south, the B1011 and B1099 St Peter’s Road to the east and
A141 to the west.
8.2. Data Collection
8.2.1. The following data collection was undertaken in 2018:
• Manual Classified Count data on Tuesday 27th March and Wednesday 28th March
• Four Automatic Traffic Count sites were surveyed over a two-week period between
Wednesday 21st March and Tuesday 3rd April
• Queue length surveys were undertaken on Tuesday 27th March at 7 highway junctions and 4
level crossing sites
• Satellite Navigation data for the March study area was collected between the 5th March 2018
and 28th March
• Car Park survey data was collected with the MCC data and also surveyed on the 12th June
• The bus routes were collected from https://www.fenland.gov.uk/busandcoach
• Signal specifications for the signalised junctions were provided by CCC
8.2.2. A site visit was undertaken on Tuesday 27th March 2018 (day of the survey) in the AM and PM Peak
periods when traffic conditions within the study area were observed.
8.3. Model Traffic Flows
8.3.1. The traffic flow profiles for the AM and PM peak period were calculated using the four ATC sites
monitored during the traffic surveys (A141, B1101 High Street, B1101 Station Road and B1099
Dartford Road), and the corresponding turning counts (MCC data).
8.3.2. The data showed the traffic flows were similar across the cumulative hours assessed. The peak hours
selected to model were 08:00 – 09:00 and 17:00 – 18:00.
8.3.3. The ATC traffic data for each site was compared to the MCC traffic flows for the AM and PM peak
periods, to ensure that the survey day was representative of typical site conditions.
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8.3.4. Within VISSIM, traffic flows need to be balanced so that within the network overall, the same amount
of traffic enters and exits the network. The survey data was utilised to produce a network of raw,
unbalanced turning movement flows in 15-minute intervals for vehicles. The unbalanced network was
then balanced between junctions. The ATC data was utilised to aid the balancing of the traffic flows.
8.3.5. Pedestrian counts across the pedestrian crossings in the town centre were surveyed using video
footage from the MCC surveys.
8.4. Model Development
8.4.1. VISSIM version 10.00-04 (most recent version) has been used to construct and run the model. The
base road network for the existing conditions VISSIM model was constructed for both peaks using
Ordnance Survey background.
8.4.2. The model is based on ‘static assignment’ throughout the network on an origin and destination basis
for each junction. Vehicle Inputs, Routes and Compositions were collated from the balanced stick
diagrams from the MCC data. The bus routes were coded in separately to the model.
8.4.3. Priority rules were placed at all give-way locations throughout the network. The signalised junction
was modelled using VisVap and PCMOVA. The level crossings were also modelled using signalised
operation.
8.5. Model Calibration / Validation
8.5.1. It is necessary to calibrate and validate the base model to confirm that the model is fit for purpose
for the evaluation of proposed improvement measures. During calibration, the network has been
checked and adjustments have been made to improve the performance of the model based on
comparisons with observed data and the site visit.
8.5.2. A number of adjustments were carried out during the calibration process including:
• Driving Behaviour and Link Types
• Speeds – speed distributions and reduced speeds
• Priority Rules
• Signals
• Pedestrians
• Random Seeds
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8.5.3. Although WebTAG does not provide explicit guidance for validation of micro-simulation models, the
overall principles applied to strategic model validation have been followed. For turning flows, the GEH
statistic has been used as a measure of model validation and observed travel times have been
compared to the modelled travel times. The acceptance criteria of modelled journey times are within
+/- 15 percent or 1 minute of surveyed journey times for 85% of routes. Observed and Modelled
queue lengths have also been compared.
8.6. Calibration / Validation Results
8.6.1. In summary in the AM Peak
• All junction movements have a GEH of under 5
• There is generally a good match between observed and modelled queue lengths
• 85% of travel times are within the validation criteria.
8.6.2. In Summary in the PM Peak
• All junction movements have a GEH of under 5
• There is generally a good match between observed and modelled queue lengths
• 88% of travel times are within the validation criteria.
Overall, taking into account all the validation data, the model is believed to be representative in the AM and PM
Peak of observed conditions and can be taken forward to be used for option testing.
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Appendices
Appendix A – AM and PM Peak traffic flows
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Appendix B – Junction output AM and PM Peak
45
Appendix C – Travel Time maps
Skanska UK
www.skanska.co.uk
Maple Cross House
Denham Way
Maple Cross
Rickmansworth
Hertfordshire
WD3 9SW
Tel: +44 (0)1923 776666
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