longbridge local model validation report issued2 · consistency. this report is an outcome of this...

Longbridge Area Action Plan Local Model Validation Report

Birmingham City Council March 2007

Prepared by: Abigail Patterson Simon Statham Graduate Consultant Senior Consultant

Rev No Comments Date 1 Jan 07 2 May 07

Beaufort House, 94/96 Newhall Street, Birmingham, B3 1PB Telephone: 0121 262 1900 Fax: 0121 262 1994 Website: http://www.fabermaunsell.com Job No 50010TBMD Reference Date Created This contains confidential and commercially sensitive information, which shall not be disclosed to third parties. f:\tp\project\50010tbmt longbridge aap\srn modelling\vissim\local model validation report\longbridge local model validation report_issued2.doc

Faber Maunsell Longbridge Area Action Plan 0

1 Introduction ..................................................................................................................... 3 1.1 Introduction ........................................................................................................... 3 1.2 Study Background................................................................................................. 3 1.3 Overview of Model Development.......................................................................... 3 1.4 Structure of Report................................................................................................ 4

2 Methodology Overview................................................................................................... 7 2.1 Introduction ........................................................................................................... 7 2.2 VISSIM Micro-simulation ...................................................................................... 7 2.3 Model Development Methodology ........................................................................ 7 2.3.1 Model Periods ....................................................................................................... 8 2.3.2 Network Development .......................................................................................... 8 2.3.3 Survey Data Collection ......................................................................................... 8 2.3.4 Travel Demand ..................................................................................................... 9 2.3.5 Model Calibration and Validation .......................................................................... 9

3 Network Development .................................................................................................. 13 3.1 Introduction ......................................................................................................... 13 3.2 Study/Network Area............................................................................................ 13 3.3 Development of Zone System ............................................................................ 13 3.4 Development of the Network .............................................................................. 14 3.5 Calibration of Network ........................................................................................ 15 3.6 Summary............................................................................................................. 15

4 Data Collection .............................................................................................................. 23 4.1 Introduction ......................................................................................................... 23 4.2 Matrix Development and Calibration................................................................... 23 4.3 Validation Data.................................................................................................... 23 4.4 Summary............................................................................................................. 23

5 Travel Demand............................................................................................................... 25 5.1 Introduction. ........................................................................................................ 25 5.2 Sources of Demand Data ................................................................................... 25 5.3 Demand User Classes........................................................................................ 25 5.4 Traffic Survey Data ............................................................................................. 25 5.5 Matrix Development ............................................................................................ 26 5.6 Validation of Matrices ......................................................................................... 26 5.7 Summary............................................................................................................. 26

6 Model Calibration and Validation ................................................................................ 28 6.1 Introduction ......................................................................................................... 28 6.2 Model Calibration ................................................................................................ 28 6.2.1 Calibration Checks.............................................................................................. 28 6.2.2 Calibration Edits.................................................................................................. 29 6.3 Model Validation ................................................................................................. 29 6.3.1 Validation Criteria................................................................................................ 29 6.3.2 Validation Results ............................................................................................... 30 6.3.3 Random Seed Variation...................................................................................... 31 6.3.4 Model Convergence............................................................................................ 32 6.4 Summary............................................................................................................. 32

7 Summary and Conclusions.......................................................................................... 34 7.1 Introduction ......................................................................................................... 34 7.2 Summary of Base Year Models .......................................................................... 34 7.4 The Way Forward ............................................................................................... 35

Appendix A Matrix Development ............................................................................................. 37

Table of Contents


Appendix B Queue Lengths ..................................................................................................... 39

Appendix C GEH Statistic and Flow Comparisons................................................................ 43

Appendix D Journey Time Comparisons................................................................................ 49

Appendix E Traffic Count Data ............................................................................................... 52

1 Introduction

Faber Maunsell Longbridge Area Action Plan

1.1 Introduction

This report describes the development and validation of micro-simulation traffic models (VISSIM) to support the development of the Longbridge Area Action Plan (AAP) which Faber Maunsell is presently contributing to on behalf of Birmingham City Council (BCC).

Following an audit by the Highways Agency consultant JMP several agreed demand elements and network changes have been made to each of the models to ensure accuracy and consistency. This report is an outcome of this re-validation of the models.

The development of the model has been carried out in accordance with the ‘Design Manual for Roads and Bridges Volume 12a Section 4’ (DMRB), and Interim Advice Note 26-01, “The Use and Application of Micro-simulation models”.

1.2 Study Background

The study seeks to assess the impact of the Longbridge Area Action Plan on the strategic highway network. The study area shown in Figure 1, encompasses the following three junctions which are the focus of the modelling:

� M5 Junction 4 � M42 Junction 1 � M42 Junction 2

It was agreed at the outset of the study, that a robust analytical traffic modelling platform would be required in order to test and assess the impact of proposals put forward by the Longbridge Area Action Plan on the strategic highway network.

It has been agreed with the stakeholders (BCC and the Highways Agency) that isolated VISSIM models would be the most appropriate way to model the impacts on the Strategic Road Network.

1.3 Overview of Model Development

Faber Maunsell’s approach to model development is founded on the application of a micro-simulation model. This type of tool has the ability to examine the impacts of road closures, junction modifications, bus priority and revised traffic circulation arrangements in detail. It is also considered that the visual ‘front-end’ of VISSIM can be used to assist public consultation and presentation phases of the work at a later date.

The development of the base models, as described in detail in this document, included the following key stages:

� Identification of the model area/coverage; � Development and identification of model zone system; � Highway network development; � Demand matrix development � Model assignment; and � Model calibration and validation.

1 Introduction


1.4 Structure of Report

This document contains seven further sections which describe the development of the base year traffic models for the Longbridge Area Action Plan and their subsequent refinement to provide a platform for future year assessments.

An overview of the methodology is provided in Section Two, which includes an introduction to VISSIM. The development of the highway network and the associated demand matrices are described in Sections Three to Five respectively and Section Six outlines the calibration and validation of the models, including a summary of the supporting validation statistics. Section Seven highlights conclusions and recommendations for the future use of the models.

2 Methodology Overview


2.1 Introduction

An overview of the model development methodology in flowchart form is shown in Figure 2.1. Each stage of the work is then summarised in the following paragraphs before being described in detail in the following sections.

2.2 VISSIM Micro-simulation

VISSIM is a microscopic traffic and transit simulation model that was originally developed at the University of Karlsruhe in the early 1970s to analyse traffic flow on motorways. After continuous development at various other Universities, PTV introduced the traffic model into a commercial environment in 1993, and it is now widely used as a foundation for transportation planning across the UK.

VISSIM allows the modelling of complex traffic operations, including various levels of transit priority treatment and railroad pre-emption at signalised intersections. This allows testing of selective vehicle detection (SVD) for any type of vehicle including buses and pedestrians for toucan crossing facilities.

VISSIM has a graphical interface that allows the user to add traffic and signal data to existing base maps of intersections and road layouts. This unique capability not only reduces the workload required for data input it also dramatically improves the quality of animation of traffic and transit operations. In contrast to other simulation models, VISSIM’s sophisticated vehicle simulation model allows the user to accurately analyse traffic transit interactions such as kerbside bus stops or complex traffic operations associated with weaving sections and merges.

The program can analyse traffic and transit operations under constraints such as lane configuration, traffic composition, traffic signals, block signals, transit stops, variable message signs, etc, thus making it a useful tool for the evaluation of various alternatives based on transportation engineering and planning measures. Besides its animation capabilities, VISSIM generated numerous user-customisable output files.

This information includes:

� Detailed travel time and delay statistics; � Queue length statistics; � Detailed signal timing information (green time, cycle length, etc); � Protocol of detector actuations and transit priority calls; � Graphical output such as time space diagram and speed profiles; and � Environmental indicators. In a similar manner to more traditional traffic modelling tools, the simulation model can be calibrated and validated using local traffic count and journey time information. This ensures that the tool is sufficiently representative of existing highway conditions before being used in the prediction of flows, queues, delays and overall journey times associated with proposed option schemes.

2.3 Model Development Methodology The type and complexity of a traffic model depends on the scale of the scheme that is proposed. It is considered that the development proposed for the area of Longbridge will result in changes to travel patterns over a wide area, through the course of a day. An appropriate methodology has therefore been developed which, in particular, is sufficiently detailed to:

2 Methodology Overview


� Understand the impact of the future schemes and developments on the SRN junctions. � Replicate observed, existing traffic flow conditions; � Identify potential traffic that might divert to alternative routes; and

The development of the traffic models has been undertaken in accordance with the DMRB Volume12a and is briefly summarised in the following paragraphs.

2.3.1 Model Periods

The three key junctions currently experience high volumes of traffic, which result in congestion and delays across the highway network. The DMRB recommends that ‘in congested urban areas the variation of travel times and costs throughout the day is complex. When modelling these areas it is usually necessary to break the day down into separate periods covering AM, PM and inter-peak periods for weekdays’. The following two periods have therefore been developed in the model platform in order to represent observed periods of distinctly different traffic conditions:

� AM Period (0800-0900); and

� PM Period (1700-1800)

The inter-peak period has not been incorporated into the modelling due to the nature of the congestion. Each junction receives a high level of traffic throughout the day; however congestion is not considered a constant problem. The models have therefore been developed to deal with the network at extreme capacity which is during the AM and PM peak periods.

In line with DMRB, care has been taken to ensure the model periods cover the whole of each period, not just the busiest hour. The two model periods are run with a 15 minute preload which enables a representative level of traffic to ‘warm up’ the network before data is collected during the designated periods.

2.3.2 Network Development

The three networks have been developed in VISSIM, through on-screen editing, based on agreed model areas, suitable zone systems, site visit inventories and traffic signal data. This stage is described in detail in Section Three.

The development of the base model networks has been undertaken using an Ordnance Survey (OS) map base over which the geometry and alignment of the networks have been constructed.

2.3.3 Survey Data Collection

A data collection exercise was undertaken at each junction in 2006. This was established as the base year.

The following data was collected and an indication of what each value was used for in the modelling process is given:

� Queue lengths (calibration); � HA link counts from the TRADS database (calibration); � Traffic turning counts (calibration and validation); and � Journey time measurements (validation)

This data formed a base for building the matrices, calibration and validation.


2.3.4 Travel Demand

The VISSIM models have been developed using a dynamic (i.e. matrix based) assignment technique. Dynamic assignment provides the ability for the model to calculate route choices from origins to destinations through a minimum cost route assignment. A dynamic assignment was selected over a static ‘fixed path’ model, as the junctions consist of numerous lane changing characteristics that are best replicated by the resulting forward thinking route choice.

Figure 2.2 provides an overview of the matrix development stages based on the agreed model areas, the zone systems (described in detail in Section Three) and the count database. The robust matrices produced describe all movements through each junction.

2.3.5 Model Calibration and Validation

Having prepared the necessary network and matrix data for the base models, the models were subjected to an iterative process of calibration and validation. This was carried out in accordance with the DMRB guidance.

Calibration is an iterative process in which the models are revised in order that the most accurate replication of the base year (2006) conditions is achieved. This included:

� Comparison between the observed and modelled link flows and queue lengths; � Revisions/remedial actions at junctions in order to ensure representative modelling of

existing conditions – including observed queue lengths; � Checks on the assigned paths between the origins and destinations; and � Further checks to ensure representative number of trips included in the matrices.

The purpose of model validation is to provide an independent demonstration that the model truly reflects existing traffic conditions. The validation procedure demonstrates the satisfactory operation of the modelling platform and ensures that the tool is both robust, and suitable, for further use and development. The DMRB contains guidance on quantifiable thresholds which the assignments should seek to achieve. Described in detail in Section Six this included an assessment of:

� Observed and modelled traffic flow data; � Statistical analysis (GEH Statistic); and � Observed and modelled journey time data.

A number of further checks were made of the developed networks and matrices through an independent audit of the traffic model carried out by JMP on behalf of the Highways Agency.


IDENTIFICATION OF MODEL AREA

IDENTIFICATION OF MODEL ZONE SYSTEM

BASE YEAR DEMAND MATRIX

DEVELOPMENT

EXISTING HIGHWAYNETWORK

DEVELOPMENT

SITE INVENTORY

SURVEYS AND TRAFFIC

SIGNAL DATA

TRAFFIC SURVEY

DATABASE, EXISTING

MODEL TOOLS AND PUBLIC TRANSPORT TIMETABLES

BASE MODEL ASSIGNMENT

BASE MODELCALIBRATION

BASE MODEL VALIDATION

VALIDATED/CALIBRATED BASE MODEL

Figure 2.1 Overview of Model Development


Convert resulting matrix to model zone system

Create fixed paths for public transport services

MATRIX VALIDATION

BASE YEAR DEMAND MATRIX DEVELOPMENT

Develop matrix using turning counts and TRADS data to determine trip ends and OD-pairs

Ensure sufficient 'demand' in matrix to enable turns and queues to validate

Identification of Model Area

Identification of Model Zone

System

Traffic Survey Database and

Public Transport

Figure 2.2 Overview of Model Matrix Development

3 Network Development


3.1 Introduction

In taking account of current and future patterns of traffic demand, the following paragraphs describe the identification of the area to be covered by the Longbridge AAP VISSIM models.

3.2 Study/Network Area

The definition of the area to be covered, and the level of detail required for each part of the model area (under both Do-Nothing and Do-Something scenarios), are important considerations in the design of a traffic model.

Three alternative approaches to modelling the motorway junctions have been considered;

� Extend the existing Longbridge VISSIM model to include the Strategic Road Network (SRN) � Develop one VISSIM model to cover the SRN � Develop individual isolated VISSIM models for SRN

The first two approaches were not considered viable. It is Faber Maunsell’s view that the existing Longbridge model is at the limits of its capability and the inclusion of the SRN would result in a model that would be too large to manage on a microscopic level and hence would not be fit for purpose.

The second option was dismissed in consideration of recent experience of modelling a number of motorway junctions in one VISSIM model. The one model approach has proven to be a time consuming and expensive process, which is justified for some large scale projects, but whilst the APP needs to be developed on a credible evidence base, it is not a detailed planning application.

On this basis, isolated VISSIM models are to be the most appropriate way to model the impacts of the SRN.

The extent and level of detail of each of the three model junctions, which has been agreed with the Client, are shown in Figures 3.1 to 3.3.

3.3 Development of Zone System

The zone system, which is used to describe the highway demand in the Study Area, can be described in terms of ‘external’ and ‘internal’ areas. In accordance with the DMRB the zone system is considered to ‘delineate the area of influence of the scheme being appraised in terms of significant traffic flow changes’.

A series of 16 zones have been identified across the three models which are suitably detailed to permit the description of traffic movements to, from and within the model areas. These are shown in Figures 3.4 to 3.6.

3 Network Development


3.4 Development of the Network

The VISSIM networks were built upon a scaled OS base map. The base mapping allowed for the road network to be modelled accurately including junction geometry, link lengths and bus stops. This data was supplemented by information obtained from the following sources:

� Site Visits - Lane allocation; - Road width - Lane Allocation; - Lane Markings; - Signal positions; and - Speed restrictions.

� Traffic signal information - Signal information was supplied directly from Birmingham City Council.

Links form either all or part of a junction, or the connections between adjacent junctions. Links are joined together by connectors. Junctions are coded by joining links and connectors to form a traffic routing decision point known as a node. These nodes represent junctions, pedestrian crossings and other lane changing opportunities.

The three junction models are a sum of the following features:

M5 Junction 4

� 5 nodes (junctions or decision points) - All of which are signal controlled nodes

� 5 zones � 4 merge and diverge points; and � 84 links and connectors M42 Junction 1 � 5 nodes (junctions or decision points)

- 3 of which is a signal controlled node - 2 of which are priority nodes

� 6 zones; � 2 merge and diverge points; and � 83 links and connectors

M42 Junction 2

� 5 nodes (junctions or decision points) - 2 of which are signal controlled nodes - 3 of which are priority nodes (onto roundabout)

� 5 zones; and � 105 links and connectors

The networks were refined to contain the appropriate traffic signal information for each model period. FM used TRANSYT to optimise the signal timings and these were transferred into the models as fixed time plans.


3.5 Calibration of Network

A series of checks were made to ensure that the base models correlated with the physical characteristics of the network in reality including:

� Range checks – the characteristics of all links were checked to ensure that they were appropriate for that class of link. Characteristics included driving behaviour, speed and number of entry lanes;

� Link lengths – the lengths of all links in the network were checked against total distance measured from an OS base map; and

� Route checks – the origins to destination routes for each vehicle type were checked for illogical routing through the network.

� Modelled queues and delays were also compared against on-site observations and local knowledge.

3.6 Summary

The above paragraphs describe the development of base year highway networks that represent SRN junctions on the edge of the Longbridge AAP study area for 2006. This has been undertaken within current guidance and recommendations, and is considered to form a robust platform for further option assessment.


Figure 3.4 M5 Junction 4 Zone Plan

4 Data Collection


4.1 Introduction

A variety of data relating to traffic movements at each motorway junction was collected as a base for model development, in terms of matrix building, calibration and validation. Traffic count data was collected for the appropriate time periods (weekday AM and PM peaks) and user classes Cars/Light Goods Vehicles (LGV) and Heavy Goods Vehicle’s (HGV). Data was gathered from external sources and in-house surveys.

4.2 Matrix Development and Calibration

Turning counts and motorway link counts were collected for the purposes of developing the demand matrices. Turning counts and motorway link counts were used to establish the various external and internal trip movements across the study areas. Link counts for the motorways were extracted from the Highways Agency’s TRADS database and Halcrow provided turning counts at each junction which were collected June 2006. These are contained in Appendix E.

Queue length data was collected as an additional check to ensure the model represents reality as much as possible. This data was collected by Faber Maunsell in January 2007. The length of queues were observed at each junction arm and at the signal heads on each gyratory.

4.3 Validation Data

Journey time surveys along with turning counts were important elements for model validation which is described in subsequent sections of this report. The journey time data consisted of 15 single direction routes. This data was collected in-house by Faber Maunsell in January 2007 during the AM and PM peak periods for the following routes;

� M5 junction 4 from junction 3/4 exit and 5/4 exit to; - A491 Sandy Lane towards Stourbridge; - A38 (N) Birmingham Road; and - A38 (S) Halesowen Road, Bromsgrove

� M42 junction 1 - M42 exit slip road to B4096 Alcester Road; - M42 exit slip road to A38 Southbound towards Bromsgrove; and - M42 exit slip road to A38 Northbound towards M5 junction 4

� M42 junction 2 from junction 1/2 exit and 3/2 exit to; - A441(N) towards Kings Norton; - Hopwood Service Station; and - A441(S) towards Redditch

4.4 Summary

The above paragraphs give a brief description of the types of data and their sources that have been used for matrix development, calibration and validation. Several data tables and a more detailed description on how the data was employed are found in Section Five.

4 Data Collection

5 Travel Demand


5.1 Introduction.

The following paragraphs describe the development of base year demand matrices for the Longbridge AAP VISSIM models based on the network and corresponding zone system highlighted in Section Three

5.2 Sources of Demand Data

The matrices were based on turning counts provided by Halcrow and motorway link counts from the Highways Agency’s TRADS database. These are contained in Appendix E.

5.3 Demand User Classes

The DMRB recommends that “the traffic model used for scheme appraisal should be capable of identifying separately the main vehicle types, whose drivers react differently to a given set of road condition”’. The VISSIM models have therefore been developed for the following three user classes.

� Cars and light goods vehicles � Heavy goods vehicles (OVG 1 & OVG 2) � Buses and coaches The first two classifications are assigned in the model via a series of trip matrices the third is based on static paths and the frequency information obtained from public transport timetables.

Various characteristics can be defined separately for the three user classes. These include information about desired speed distributions in speed limit areas; reduced speed distribution on corners; and acceleration and deceleration features.

5.4 Traffic Survey Data

The following traffic count data was collated for the appropriate time periods and user classes.

Table 5.1. Summary of Traffic Count Data

Location Type Direction Date

M5 near junction 4 Link Both 2006



M5/Sandy Lane/Birmingham Road/ Halesowen Road Turning Count All June 2006

M42 /B4096 Alcester Road/A38 (S)/A38 (N)/ B4096 Old Birmingham Road

Turning Count All June 2006

M42/A441 (N)/ A441 (S)/ Hopwood Services Turning Count All June 2006

5 Travel Demand


5.5 Matrix Development

Turning Counts and TRADS data were used to determine external to external movements in the matrices. This data provided the origin and destination levels and the known movements round each junction.

The following table shows the final matrix totals for each model. Full matrices are included in Appendix A:

Table 5.2 Matrix Totals

Model Cars and LGV Totals HGV Totals

M5 Junction 4 AM

M5 Junction 4 PM

9282

8971

1748

1484

M42 Junction 1 AM

M42 Junction 1 PM

10108

10552

1603

1164

M42 Junction 2 AM

M42 Junction 2 PM

8600

8320

1706

1639

5.6 Validation of Matrices

All stages of the trip matrix development were checked and recorded and, following assignment to the corresponding networks, comparisons were made between modelled and observed data.

5.7 Summary

This section described the development of the base year demand matrices which represents movements through each of the three motorway junctions in the Longbridge study area in 2006. This has been taken in accordance with the current guidance and recommendations and is considered to form a robust platform for the model assignment.


6 Model Calibration and Validation


6.1 Introduction

The following section summarises the calibration and validation of the base year VISSIM models in accordance with current guidance. Although undertaken using independent sources of data, the calibration and validation of the models form an iterative process leading to the demonstration of a robust platform for future year development.

6.2 Model Calibration

The purpose of model calibration is to ensure that the model assignments are appropriate. Calibration is an iterative process, in which the model is continually revised to ensure that, in the AM and PM peak periods:

� Traffic patterns throughout the study area are modelled accurately, including the paths selected;

� Key junctions are modelled accurately in terms of vehicle behaviour, especially at stop lines and lane changing; and

� Traffic volumes on the roads are modelled accurately.

6.2.1 Calibration Checks

The following calibration checks were undertaken for each model period:

� Checking the coding of the network – Assignment of the full matrix to the base models provided a comprehensive check of the network. This enabled the construction of the junctions to be checked and also highlighted any programme error files which needed to be addressed. Any identified errors were subsequently corrected.

� Measures of calibration – To demonstrate that the model was working correctly comparisons were made between observed and modelled queue lengths.

In representing observed queue lengths, modelled vehicle numbers were calibrated within a difference of 10 cars of the observed numbers. In the majority of cases the modelled queue lengths replicated observed lengths. The table below gives the percentage of counts in each model that were within 10 cars. The full results of the queue length comparisons are found in Appendix B.

Model % of counts with a difference of <10 vehicles

M5 Junction 4 AM Peak 100%

M5 Junction 4 PM Peak 100%





6 Model Calibration and Validation


6.2.2 Calibration Edits

Having identified how the initial model compared with the calibration tests, as series of edits were made to the network and demand elements of VISSIM in order to improve the correlation between the observed and synthesised data. The following edits were made to the network:

� Removed erroneous paths � Appropriate gap acceptance at give way lines; and

6.3 Model Validation

6.3.1 Validation Criteria

In order to demonstrate that the models provided a robust platform for option testing and development it was necessary to show that the base models accurately represented observed conditions. Validation checks included:

� Network validation/checks (previously discussed); � Matrix validation/checks (previously discussed); � Link flow validation and statistical criteria; and � Overall model validation (e.g. journey time surveys).

The DMRB specifies the acceptable values for modelled and observed flow comparisons and suggests how the validation should relate to the magnitude of the values being compared. A summary is included in the table below:

Table 6.1 Model Validation Criteria (1)

Criteria and Measures Acceptability Guideline

Assigned Hourly Flows (e.g. links or turning movements): compared with observed flows:

1. Individual flows within 100vph for flows <700vph )

2. Individual flows within 15% for flows 700-2700vph ) >85% of cases

3. Individual flows within 400vph for flows >2700 )

Percentage differences between observed and modelled data sets can prove to be misleading given the relative value of the difference. The standard method used to compare modelled values against observations on a link involves the calculation of the Geoff Havers (GEH) statistic, which is a form of the Chi-squared statistic, incorporating both relative and absolute errors.

The GEH is a measure of comparability that takes account of, not only the difference between the observed and modelled flows, but also the significance of this difference with respect to the size of the observed flow. For instance, a difference of 50% compared to an observed flow of 10 is of far less significance that a difference of 20% compared with an observed flow of 1000. The GEH is calculated as follows:

GEH = �

As a rule of thumb in comparing assigned volumes with observed volumes a GEH parameter of 5 of less indicates an acceptable fit whilst a value greater than 10 requires closer attention. Guidance in the DMRB sets out the following criteria:

(M-C)2 (M + C)/2

Where: M is the modelled flow C is the observed flow




GEH Statistic: i) Individual flows GEH <5 >85% of cases

The best measure of the overall performance of the model is to consider particular journey times through the assigned network and compare the known observed travel times with those predicted by the model. This combines the delays which are simulated at each junction along the route and therefore presents a good indication of the overall correspondence between known and replicated movements. Guidance in the DMRB sets out the following criteria:



Modelled journey times compared with observed times:

Times within 15% (or one minute if higher) >85% of routes

6.3.2 Validation Results

The three models were validated for total traffic flows under demand conditions which sought to enter the network over the one hour AM and PM period. For this reason, a 15 minute build up period was included in order to allow traffic to enter the network, thereby giving a more representative set of validation results in terms of link counts for the peak hour.

All models have been converged on edge and path travel times and volume.

The following paragraphs summarise the validation of the Longbridge models against the above criteria.

6.3.2.1 Traffic Flow Comparisons

The observed modelled flows were compared for each of the validation counts in accordance with the criteria above. The permissible distance was calculated for each value (based on the observed figure) and compared with that which had been modelled. The full results are included in Appendix C and are summarised in Table 6.4 below:

Figure 6.4 Summary of Traffic Flow Validation

Model % of validation sites meeting the criteria that: Individual flows within 100vph for flows <700vph

M5 Jnc.4 AM 100%

M5 Jnc.4 PM 100%

M42 Jnc.1 AM 100%

M42 Jnc.1 PM 95%

M42 Jnc.2 AM 100%

M42 Jnc.2 PM 100%

NB DMRB Target >85%

For the AM and PM periods of each model, the modelled turning movement flows achieves the DMRB 85% criteria, demonstrating the modelled flows correspond well with the observed on site data.


6.3.2.2 GEH Statistic Comparisons

The calculated GEH statistics for the observed and modelled flows were considered for each of the validation counts in accordance with the above criteria. The full results are included in Appendix C and are summarised in Table 6.5 below:

Table 6.5 Summary of GEH Validation

Model % of validation sites with GEH <5

LIGHTS

% of validation sites with GEH <5

HGV’s

M5 J/nc.4 AM 100% 100%

M5 Jnc.4 PM 100% 100%

M42 Jnc.1 AM 100% 100%

M42 Jnc.1 PM 100% 100%

M42 Jnc2 AM 100% 100%

M42 Jnc.2 PM 100% 100%

NB DMRB Target >85%

The output from the GEH statistical comparison shows all models have over 85% of the turning counts under 5 GEH. This is a further demonstration of the strength of the validation. The use of turning counts rather than selected link or cordon counts for validation demonstrates the model represents the correct distribution of traffic as well as the correct flows.

The data points used for the GEH Statistic Comparisons were the same as those used for the Traffic Flow Comparisons.

6.3.2.3 Journey Time Comparisons

The full results of the journey time comparisons are included in Appendix D and are summarised in Table 6.6 below:

Table 6.6 Summary of Journey Time Validation

Model % of ‘links’ with modelled time being within 15% (or 1 minute if higher) than observed

M5 Jnc.4 AM 100%

M5 Jnc.4 PM 100%

M42 Jnc.1 AM 100%

M42 Jnc.1 PM 100%

M42 Jnc.2 AM 100%

M42 Jnc.2 PM 100%

NB DMRB Target >85%

The AM and PM results of the journey time comparisons show the validation to be acceptable in regard to the DMRB criteria. All model journey times correspond well with those observed on site

6.3.3 Random Seed Variation

The model validations were carried out under a random seed assignment of 42. The random seed number controls the nature in which traffic enters onto the network from a zone. This


provides a useful test to examine the sensitivity of the model to changes in traffic flow conditions. Random seeds of 32 and 52 were therefore used. The validation tests were carried out on these outputs to demonstrate the stability of the model platform. The results of which are shown in Table 6.7 below:

Table 6.7 Random Seed Variation Results

Model Seed Flow Validation GEH Validation Journey Time Validation

M5 Jnc.1 AM

32

52

96%

96%

100%

100%

100%

100%

M5 Jnc.1 PM

32

52

100%

100%

100%

100%

100%

100%

M42 Jnc.1 AM

32

52

100%

100%

100%

100%

100%

100%

M42 Jnc.1 PM

32

52

95%

95%

100%

100%

100%

100%

M42 Jnc.2 AM

32

52

100%

100%

100%

100%

100%

100%

M42 Jnc.2 PM

32

52

100%

100%

100%

100%

100%

100%

6.3.4 Model Convergence

As stated previously, the models have used a dynamic assignment method to accurately represent lane changing characteristics. As there is only one route from each origin-destination pair the convergence of each of the models is 100%.

6.4 Summary It can be seen from the above tables that the three Longbridge models validate well in all modelled periods and at various random seeds. This gave Faber Maunsell a sound platform on which to develop future year scenarios for the Longbridge Study Area.

7 Summary and Conclusions


7.1 Introduction

It was decided that the VISSIM micro-simulation software was the most sensible approach to examine the potential impact of the Longbridge Area Action Plan on the Strategic Road Network.

All three motorway junctions are relatively congested sites, therefore in accordance with DMRB recommendations; two separate model periods were created to represent AM and PM weekday traffic conditions.

7.2 Summary of Base Year Models

Once the study area for this project had been established and site visits had been conducted Faber Maunsell were able to construct three motorway junction networks and zone systems in to the VISSIM interface with the aid of scaled OS maps.

Each model was calibrated to ensure robust results. This entailed checks and improvements on the coding of the network and comparisons of observed and modelled counts. This iterative process continued until the modelling team were happy that reliable and robust base models were being carried forward. Faber Maunsell subsequently validated each model in accordance with DMRB Guidelines. The base year models were developed for 2006 traffic conditions, covering;

� AM Peak (08:00 – 09:30) � PM Peak (17:00 – 18:00)

Table 7.1 Base Model Summary Data

Model Total 2006

M5 Junction 4 Total Number of:

Nodes (junctions)

Links & Connectors

Zones

5

86

5

Total Trip Ends (lights and heavies combined):

AM

PM

11030

10455

M42 Junction 1 Total Number of :

Nodes (junctions)

Links & Connectors

Zones

4

83

6


AM

PM

11711

11716

M42 Junction 2 Total Number of:

Nodes (junctions)

5

7 Summary and Conclusions


Links & Connectors

Zones

105

5


AM

PM

10306

9959

7.3 Base Year Network Performance

Table 7.2 below shows a summary of the overall performance of the model networks. This will be useful when comparing the base year models against future year option tests. The data shows the average for all vehicles that have passed through the network, including through trips on the motorway.

Junction Time Period

Average Speed (kph)

Average Delay

(seconds) AM 63.9 22.4 M42 Junction 1 PM 60.4 29.9 AM 82.4 12.2 M42 Junction 2 PM 79.6 15.9 AM 62.6 25.2 M5 Junction 4 PM 54.0 38.1

7.4 The Way Forward

The VISSIM models developed meet the criteria set in current guidance and practice. They can therefore be taken forward with confidence as a suitable tool for a future testing. The document should form a reference for any further use of the model.

Appendices


APPENDIX AMATRIX DEVLOPMENT

M5 Junction 4 AM Peak 08:00- 09:00

LIGHTS 1 2 3 4 5 HGV's 1 2 3 4 51 0 198 337 2027 90 1 0 23 49 650 162 155 0 211 292 138 2 10 0 17 15 153 550 246 0 87 140 3 31 14 0 1 254 2841 317 27 0 470 4 693 21 2 0 525 208 129 240 579 0 5 8 7 38 61 0

9282 1748

M5 Junction 4PM Peak 17:00-18:00

LIGHTS 1 2 3 4 5 HGV's 1 2 3 4 51 0 278 869 1538 425 1 0 5 9 531 02 52 0 275 349 176 2 5 0 4 5 03 398 88 0 50 326 3 18 0 0 1 54 2083 338 54 0 877 4 846 1 0 0 245 50 198 246 301 0 5 1 5 6 18 0

8971 1484

M42 Junction 1 AM Peak 08:00- 09:00

LIGHTS 1 2 3 4 5 6 HGV's 1 2 3 4 5 61 0 3456 0 0 0 0 1 0 665 0 0 0 02 3650 0 109 10 33 319 2 702 0 12 2 2 273 0 283 0 15 141 696 3 0 8 0 5 4 764 0 33 1 0 51 198 4 0 5 4 0 0 25 0 39 131 25 0 21 5 0 3 5 0 0 06 0 296 387 207 6 0 6 0 24 49 8 0 0

10108 1603

Appendix A Matrix Development



LIGHTS 1 2 3 4 5 6 HGV's 1 2 3 4 5 61 0 3172 0 0 0 0 1 0 586 0 0 0 02 3713 0 289 37 53 534 2 509 0 1 0 0 203 0 129 0 16 203 809 3 0 3 0 0 3 164 0 14 6 0 44 193 4 0 1 0 0 1 05 0 58 157 28 0 10 5 0 0 4 0 0 16 0 227 575 278 7 0 6 0 4 14 1 0 0

10552 1164

M42 Junction 2AM Peak 08:00- 09:00

LIGHTS 1 2 3 4 5 HGV's 1 2 3 4 51 0 25 501 318 145 1 0 4 36 11 52 12 0 3 21 118 2 5 0 1 1 173 352 87 0 103 2836 3 26 28 0 13 7454 358 68 56 0 252 4 19 1 7 0 195 152 139 2848 206 0 5 18 22 706 22 0

8600 1706


LIGHTS 1 2 3 4 5 HGV's 1 2 3 4 51 0 22 271 403 146 1 0 1 9 6 132 14 0 3 26 114 2 1 0 0 0 163 730 103 0 105 2758 3 18 25 0 5 7514 355 44 86 0 207 4 3 0 4 0 75 131 109 2487 206 0 5 5 23 746 6 0

8320 1639


APPENDIX B - Queue Lengths (Number of Vehicles)M5 Junction 4 AM PEAK

M5 SOUTHBOUND EXIT SLIP ROAD A 38 BIRMINGHAM ROAD A 38 HALESOWEN ROADCounter 1 Count 2 Counter 3

Observed Modelled Observed Modelled Observed ModelledTime Q length Q length Time Q length Q length Time Q length Q length

1st Quarter Average 4 2 Average 3 4 Average 7 92nd Quarter Average 9 3 Average 4 4 Average 12 93rd Quarter Average 6 3 Average 2 3 Average 3 64th Quarter Average 5 2 Average 3 5 Average 4 5

M5 NORTHBOUND EXIT SLIP ROAD A 491 SANDY LANECount 4 Count 5

Observed Modelled Observed ModelledTime Q length Q length Time Q length Q length

1st Quarter Average 5 4 Average 8 152nd Quarter Average 10 5 Average 9 153rd Quarter Average 7 6 Average 5 144th Quarter Average 6 6 Average 4 9

M5 Junction 4 PM PEAKM5 SOUTHBOUND EXIT SLIP ROAD A 38 BIRMINGHAM ROAD A 38 HALESOWEN ROADCounter 1 Count 2 Counter 3



M5 NORTHBOUND EXIT SLIP ROAD A 491 SANDY LANECount 4 Count 5



Appendix B Queue Lengths


M42 J1 AM PEAK

M42 GYRATORY JCN M42 EXIT M 42 EXIT SLIP ROAD GYRATORY B4 JCN A38 FROM BROMSGROVECounter 1 Count 2 Count 3



A 38 FROM BROMSGROVE GYRATORY B4 JCN A 38 FROM M5 Jcn 4 A 38 FROM M5Count 4 Count 5 Count 6



B 4096 Old Birmingham Road B 4096 Alcester RoadCount 7 Count 8 + 9




M42 Junction 1 PM PEAK

M42 GYRATORY JCN M42 EXIT M 42 EXIT SLIP ROAD GYRATORY B4 JCN A38 FROM BROMSGROVECount 1 Count 2 Count 3



A 38 FROM BROMSGROVE GYRATORY B4 JCN A 38 FROM M5 Jcn 4 A 38 FROM M5 Jcn 4Count 4 Count 5 Count 6



A 4096 Old Birmingham Road A 4096 Alcester RoadCount 7 Count 8+9




M42 Junction 2 AM PEAKA441 NORTH Service Station Exit M5 Westbound Exit SlipCounter 1 Count 2 Counter 3



A441 South M5 Eastbound Exit SlipCount 4 Count 5

Observed Modelled Observed ModelledTime Q length Time Q length


M42 Junction 2 PM PEAKA441 NORTH Service Station Exit M5 Westbound Exit SlipCounter 1 Count 2 Counter 3



A441 South M5 Eastbound Exit SlipCount 4 Count 5

Observed Modelled Observed ModelledTime Q length Time Q length



M5 JUNCTION 4 - AM PEAK

AM ValidationCARS/LGV HGV

Movement From To Obs. Modelled GEH Diff. ClassTarget

Diff.N/Y Movement Obs. Modelled GEH Diff.

1 M5 Sbound Off Slip A38 N 198 197 0.1 1 1 100 Y 1 23 23 0.0 02 M5 Sbound Off Slip A38 S 337 341 0.2 -4 1 100 Y 2 49 47 0.3 23 M5 Sbound Off Slip M5 South 0 0 0 1 100 Y 3 0 0 04 M5 Sbound Off Slip A491 90 91 0.1 -1 1 100 Y 4 16 16 0.0 05 M5 Sbound Off Slip M5 North 0 0 0 1 100 Y 5 2 0 2.0 26 A38 N A38 S 211 210 0.1 1 1 100 Y 6 17 15 0.5 27 A38 N M5 South 292 296 0.2 -4 1 100 Y 7 15 15 0.0 08 A38 N A491 138 139 0.1 -1 1 100 Y 8 15 16 0.3 -19 A38 N M5 North 155 158 0.2 -3 1 100 Y 9 10 9 0.3 1

10 A38 N A38 N 0 0 1 100 Y 10 0 0 011 A38 S M5 South 112 86 2.6 26 1 100 Y 11 1 1 0.0 012 A38 S A491 180 143 2.9 37 1 100 Y 12 25 25 0.0 013 A38 S M5 North 556 550 0.3 6 1 100 Y 13 31 31 0.0 014 A38 S A38 N 262 246 1.0 16 1 100 Y 14 14 10 1.2 415 A38 S A38 S 0 0 1 100 Y 15 0 0 016 M5 Nbound Off Slip A491 470 468 0.1 2 1 100 Y 16 52 55 0.4 -317 M5 Nbound Off Slip M5 North 0 0 0 1 100 Y 17 0 0 018 M5 Nbound Off Slip A38 N 317 324 0.4 -7 1 100 Y 18 21 22 0.2 -119 M5 Nbound Off Slip A38 S 27 28 0.2 -1 1 100 Y 19 2 2 0.0 020 M5 Nbound Off Slip M5 South 0 0 1 100 Y 20 0 0 021 A491 M5 North 208 209 0.1 -1 1 100 Y 21 8 8 0.0 022 A491 A38 N 129 130 0.1 -1 1 100 Y 22 7 8 0.4 -123 A491 A38 S 240 248 0.5 -8 1 100 Y 23 38 39 0.2 -124 A491 M5 South 579 584 0.2 -5 1 100 Y 24 61 64 0.4 -325 A491 A492 0 0 0 1 100 Y 25 0 026 M5 Northbound Under Junction 2841 2855 0.3 -14 1 100 Y 26 650 690 1.5 -4027 M5 Southbound Under Junction 2027 2020 0.2 7 1 100 Y 27 639 652 0.5 -13

100% 100% 100.0%<5 GEH Flow Comparison <5 GEH

Flow Comparisons

Appendix C GEH Statistic and Flow Comparisons


M5 JUNCTION 4 - PM PEAK

PM ValidationCARS/LGV HGV



1 M5 Sbound Off Slip A38 N 278 280 0.1 -2 1 100 Y 1 5 5 0.0 02 M5 Sbound Off Slip A38 S 869 862 0.2 7 1 100 Y 2 9 9 0.0 03 M5 Sbound Off Slip M5 South 0 0 0 1 100 Y 3 0 0 04 M5 Sbound Off Slip A491 425 432 0.3 -7 1 100 Y 4 0 0 05 M5 Sbound Off Slip M5 North 0 0 0 1 100 Y 5 0 0 06 A38 N A38 S 275 278 0.2 -3 1 100 Y 6 4 4 0.0 07 A38 N M5 South 349 341 0.4 8 1 100 Y 7 5 5 0.0 08 A38 N A491 176 176 0.0 0 1 100 Y 8 0 0 09 A38 N M5 North 52 52 0 0 1 100 Y 9 5 5 0.0 0

10 A38 N A38 N 0 0 1 100 Y 10 0 0 011 A38 S M5 South 50 50 0.0 0 1 100 Y 11 1 1 0.0 012 A38 S A491 326 324 0.1 2 1 100 Y 12 5 5 0.0 013 A38 S M5 North 398 401 0.2 -3 1 100 Y 13 18 16 0.5 214 A38 S A38 N 88 89 0.1 -1 1 100 Y 14 0 0 015 A38 S A38 S 0 0 1 100 Y 15 0 0 016 M5 Nbound Off Slip A491 877 848 1.0 29 1 100 Y 16 24 23 0.2 117 M5 Nbound Off Slip M5 North 0 0 0 1 100 Y 17 0 0 018 M5 Nbound Off Slip A38 N 338 346 0.4 -8 1 100 Y 18 1 1 0.0 019 M5 Nbound Off Slip A38 S 54 53 0.1 1 1 100 Y 19 0 0 020 M5 Nbound Off Slip M5 South 0 0 1 100 Y 20 0 0 021 A491 M5 North 50 51 0.1 -1 1 100 Y 21 1 1 0.0 022 A491 A38 N 198 203 0.4 -5 1 100 Y 22 5 5 0.0 023 A491 A38 S 256 246 0.6 10 1 100 Y 23 6 6 0.0 024 A491 M5 South 301 299 0.1 2 1 100 Y 24 18 17 0.225 A491 A492 0 0 0 1 100 Y 25 0 026 M5 Northbound Under Junction 2083 2097 0.3 -14 1 100 Y 26 846 843 0.1 327 M5 Southbound Under Junction 1538 1540 0.1 -2 1 100 Y 27 531 533 0.1 -2


Flow Comparisons



AM ValidationCARS/LGV HGV



1 A38(N) B4096(N) 15 17 0.5 -2 1 100 Y 1 5 6 0.4 -12 A38(N) M42(E) 283 289 0.4 -6 1 100 Y 2 8 9 0.3 -13 A38(N) B4096(S) 141 143 0.2 -2 1 100 Y 3 4 4 0.0 04 A38(N) A38(S) 696 708 0.5 -12 1 100 Y 4 76 76 0.0 05 A38(N) A38(N) 0 0 5 0 06 A38(S) A38(N) 496 395 4.8 101 1 100 N 6 51 51 0.0 07 A38(S) B4096(N) 262 207 3.6 55 1 100 Y 7 8 7 0.4 18 A38(S) M42(E) 353 303 2.8 50 1 100 Y 8 25 23 0.4 29 A38(S) B4096(S) 6 6 0.0 0 1 100 Y 9 0 0 0

10 A38(S) A38(S) 0 0 10 0 011 B4096(S) A38(S) 21 20 0.2 1 1 100 Y 11 0 0 012 B4096(S) A38(N) 131 125 0.5 6 1 100 Y 12 5 5 0.0 013 B4096(S) B4096(N) 25 24 0.2 1 1 100 Y 13 0 0 014 B4096(S) M42(E) 39 35 0.7 4 1 100 Y 14 3 3 0.0 015 B4096(S) B4096(S) 0 0 15 0 016 M42(E) B4096(S) 33 33 0.0 0 1 100 Y 16 2 2 0.0 017 M42(E) A38(S) 319 321 0.1 -2 1 100 Y 17 27 27 0.0 018 M42(E) A38(N) 109 109 0.0 0 1 100 Y 18 12 13 0.3 -119 M42(E) B4096(N) 10 10 0.0 0 1 100 Y 19 2 2 0.0 020 M42(E) M42(E) 0 0 20 0 021 B4096(N) M42(E) 33 32 0.2 1 1 100 Y 21 5 5 0.0 022 B4096(N) B4096(S) 51 50 0.1 1 1 100 Y 22 0 0 023 B4096(N) A38(S) 198 198 0.0 0 1 100 Y 23 2 2 0.0 024 B4096(N) A38(N) 1 1 0.0 0 1 100 Y 24 4 4 0.0 025 B4096(N) B4096(N) 0 0 25 0 0

100.0% 100% 100.0%<5 GEH Flow Comparison <5 GEH

Flow Comparisons



PM ValidationCARS/LGV HGV



1 A38(N) B4096(N) 14 16 0.5 -2 1 100 Y 1 0 0 02 A38(N) M42(E) 113 133 1.8 -20 1 100 Y 2 3 3 0.0 03 A38(N) B4096(S) 177 204 2.0 -27 1 100 Y 3 3 3 0.0 04 A38(N) A38(S) 706 828 4.4 -122 1 100 N 4 15 16 0.3 -15 A38(N) A38(N) 0 0 5 0 0 06 A38(S) A38(N) 703 585 4.6 118 1 100 N 6 23 14 2.1 97 A38(S) B4096(N) 328 274 3.1 54 1 100 Y 7 2 1 0.8 18 A38(S) M42(E) 275 224 3.2 51 1 100 Y 8 5 3 1.0 29 A38(S) B4096(S) 6 7 0.4 -1 1 100 Y 9 0 0 0

10 A38(S) A38(S) 0 0 10 0 0 011 B4096(S) A38(S) 10 0 4.5 10 1 100 Y 11 1 0 1.4 112 B4096(S) A38(N) 157 157 0.0 0 1 100 Y 12 4 1 1.9 313 B4096(S) B4096(N) 28 26 0.4 2 1 100 Y 13 0 0 014 B4096(S) M42(E) 58 55 0.4 3 1 100 Y 14 0 0 015 B4096(S) B4096(S) 0 0 15 0 016 M42(E) B4096(S) 50 52 0.3 -2 1 100 Y 16 0 0 017 M42(E) A38(S) 505 533 1.2 -28 1 100 Y 17 19 19 0.0 018 M42(E) A38(N) 274 280 0.4 -6 1 100 Y 18 1 1 0.0 019 M42(E) B4096(N) 35 36 0.2 -1 1 100 Y 19 0 0 020 M42(E) M42(E) 0 0 20 0 0 021 B4096(N) M42(E) 14 14 0.0 0 1 100 Y 21 1 1 0.0 022 B4096(N) B4096(S) 44 44 0.0 0 1 100 Y 22 1 1 0.0 023 B4096(N) A38(S) 193 188 0.4 5 1 100 Y 23 0 0 024 B4096(N) A38(N) 6 5 0.4 1 1 100 Y 24 0 0 025 B4096(N) B4096(N) 0 0 25 0 0 0

100.0% 95.00% 100.0%<5 GEH Flow Comparison <5 GEH

Flow Comparisions



AM ValidationCARS/LGV Flow Comparison HGV



1 A441 North Service Station 25 25 0.0 0 1 100 Y 1 4 4 0.0 02 A441 North M5 Eastbound (On Slip) 501 495 0.3 6 1 100 Y 2 36 34 0.3 23 A441 North A441 South 318 309 0.5 9 1 100 Y 3 11 11 0.0 04 A441 North M5 Westbound (On Slip) 145 146 0.1 -1 1 100 Y 4 5 5 0.0 05 A441 North A441 North (U Turn) 0 0 1 100 Y 5 0 0 06 Service Station M5 Eastbound 3 3 0.0 0 1 100 Y 6 1 1 0.0 07 Service Station A441 South 21 22 0.2 -1 1 100 Y 7 1 1 0.0 08 Service Station M5 Westbound 118 117 0.1 1 1 100 Y 8 17 17 0.0 09 Service Station A441 North 12 13 0.3 -1 1 100 Y 9 5 5 0.0 0

10 Service Station Service Station 0 0 0 1 100 Y 10 0 0 011 M5 Westbound (Off Slip) A441 South 103 105 0.2 -2 1 100 Y 11 13 15 0.5 -212 M5 Westbound (Off Slip) M5 Westbound 0 0 1 100 Y 12 0 0 013 M5 Westbound (Off Slip) A441 North 352 349 0.2 3 1 100 Y 13 26 28 0.4 -214 M5 Westbound (Off Slip) Service Station 87 84 0.3 3 1 100 Y 14 28 27 0.2 115 M5 Westbound (Off Slip) M5 Eastbound (On Slip) 0 0 1 100 Y 15 0 0 016 A441 South M5 Westbound 252 253 0.1 -1 1 100 Y 16 19 18 0.2 117 A441 South A441 North 358 362 0.2 -4 1 100 Y 17 19 18 0.2 118 A441 South Service Station 68 68 0.0 0 1 100 Y 18 1 1 0.0 019 A441 South M5 Eastbound (On Slip) 56 56 0.0 0 1 100 Y 19 7 7 0.0 020 A441 South A441 South 0 0 1 100 Y 20 0 0 021 M5 Eastbound (Off Slip) A441 North 152 149 0.2 3 1 100 Y 21 18 18 0.0 022 M5 Eastbound (Off Slip) Service Station 139 139 0.0 0 1 100 Y 22 22 22 0.0 023 M5 Eastbound (Off Slip) M5 Eastbound (On Slip) 0 0 0 1 100 Y 23 0 0 024 M5 Eastbound (Off Slip) A441 South 206 205 0.1 1 1 100 Y 24 22 23 0.2 -125 M5 Eastbound (Off Slip) M5 Wesbound (On Slip) 0 0 0 1 100 Y 25 0 0 026 M5 Easbound Under Junction 2848 2871 0.4 -23 1 100 Y 26 706 713 0.3 -727 M5 Wesbound Under Junction 2836 2835 0.0 1 1 100 Y 27 745 743 0.1 2




PM ValidationCARS/LGV Flow Comparison HGV



1 A441 North Service Station 22 22 0.0 0 1 100 Y 1 1 1 0.0 02 A441 North M5 Eastbound (On Slip) 271 271 0.0 0 1 100 Y 2 9 9 0.0 03 A441 North A441 South 403 402 0.0 1 1 100 Y 3 6 6 0.0 04 A441 North M5 Westbound (On Slip) 146 148 0.2 -2 1 100 Y 4 13 14 0.3 -15 A441 North A441 North (U Turn) 0 0 0 1 100 Y 5 0 0 06 Service Station M5 Eastbound 3 3 0.0 0 1 100 Y 6 0 0 07 Service Station A441 South 26 26 0.0 0 1 100 Y 7 0 0 08 Service Station M5 Westbound 114 116 0.2 -2 1 100 Y 8 16 16 0.0 09 Service Station A441 North 14 14 0.0 0 1 100 Y 9 1 1 0.0 0

10 Service Station Service Station 1 0 1.4 1 1 100 Y 10 0 0 011 M5 Westbound (Off Slip) A441 South 105 107 0.2 -2 1 100 Y 11 5 6 0.4 -112 M5 Westbound (Off Slip) M5 Westbound 0 0 0 1 100 Y 12 0 0 013 M5 Westbound (Off Slip) A441 North 730 732 0.1 -2 1 100 Y 13 18 19 0.2 -114 M5 Westbound (Off Slip) Service Station 103 105 0.2 -2 1 100 Y 14 25 26 0.2 -115 M5 Westbound (Off Slip) M5 Eastbound (On Slip) 3 0 2.4 3 1 100 Y 15 0 0 016 A441 South M5 Westbound 207 206 0.1 1 1 100 Y 16 7 5 0.8 217 A441 South A441 North 355 346 0.5 9 1 100 Y 17 3 3 0.0 018 A441 South Service Station 44 42 0.3 2 1 100 Y 18 0 0 019 A441 South M5 Eastbound (On Slip) 86 82 0.4 4 1 100 Y 19 4 5 0.5 -120 A441 South A441 South 1 0 1.4 1 1 100 Y 20 0 0 021 M5 Eastbound (Off Slip) A441 North 131 130 0.1 1 1 100 Y 21 5 4 0.5 122 M5 Eastbound (Off Slip) Service Station 109 106 0.3 3 1 100 Y 22 23 22 0.2 123 M5 Eastbound (Off Slip) M5 Eastbound (On Slip) 0 0 0 1 100 Y 23 0 0 024 M5 Eastbound (Off Slip) A441 South 206 202 0.3 4 1 100 Y 24 6 6 0.0 025 M5 Eastbound (Off Slip) M5 Wesbound (On Slip) 0 0 0 1 100 Y 25 0 0 026 M5 Easbound Under Junction 2487 2506 0.4 -19 1 100 Y 26 746 752 0.2 -627 M5 Wesbound Under Junction 2857 2760 1.8 97 1 100 Y 27 751 747 0.1 4



M5 JUNCTION 4 - AM PEAKM5 Southbound

Movement/RouteAverage VISSIM Time (s)

Obs. Time (s)

Difference (s)

% DifferenceModel

Within 15%

Model Within 1

minValidated

M5 - A491 96.4 103 6.43 -6% Y Y Y

M5 - A38 N 53.2 48 -5.37 11% N Y Y

M5 A38 S 56.8 62 4.87 -8% Y Y Y

M5 Northbound


Obs. Time (s)

Difference (s)

% DifferenceModel

Within 15%

Model Within 1

minValidated

M5 - A491 44.9 43 -1.73 4% Y Y Y

M5 - A38 N 92.9 122 28.77 -24% N Y Y

M5 A38 S 120.1 112 -8.43 8% Y Y Y

100%M5 JUNCTION 4 - PM PEAKM5 Southbound


Obs. Time (s)

Difference (s)

% DifferenceModel

Within 15%

Model Within 1

minValidated

M5 - A491 83.6 127 43.54 -34% N Y Y

M5 - A38 N 38.2 65 26.80 -41% N Y YM5 A38 S 43 79 35.50 -45% N Y Y

M5 Northbound


Obs. Time (s)

Difference (s)

% DifferenceModel

Within 15%

Model Within 1

minValidated

M5 - A491 108.4 58 -50.40 87% N Y Y

M5 - A38 N 124.1 71 -52.77 74% N Y YM5 A38 S 144.9 107 -37.90 35% N Y Y

100%

Appendix D Journey Time Comparisons




Obs. Time (s)

Difference (s)

% DifferenceModel

Within 15%

Model Within 1

minValidated

M42-B4096(S) 78 73 -4.60 6% Y Y Y

M42-A38(S) 75 114 39.15 -34% N Y Y

M42-A38(N) 84 74 -9.63 13% Y Y Y

100%



Obs. Time (s)

Difference (s)

% DifferenceModel

Within 15%

Model Within 1

minValidated

M42-B4096(S) 90.3 34 -56.30 166% N Y Y

M42-A38(S) 82.05 43 -39.05 91% N Y YM42-A38(N) 84.325 58 -26.33 45% N Y Y

100%




Obs. Time (s)

Difference (s)

% DifferenceModel

Within 15%

Model Within 1

minValidated

M42 - A441 (N) 39.1 55 16.23 -29% N Y Y

M42 - Services 45.1 63 17.73 -28% N Y Y

M42 - A441 (S) 62.8 83 19.91 -24% N Y Y

M42 Westbound


Obs. Time (s)

Difference (s)

% DifferenceModel

Within 15%

Model Within 1

minValidated

M42 - A441 (N) 84 95 11.17 -12% Y Y Y

M42 - Services 83.6 48 -35.43 74% N Y YM42 - A441 (S) 49.1 82 32.73 -40% N Y Y

100%



Obs. Time (s)

Difference (s)

% DifferenceModel

Within 15%

Model Within 1

minValidated

M42 - A441 (N) 48.5 43 -6.00 14% Y Y Y

M42 - Services 66.9 42 -24.50 58% N Y YM42 - A441 (S) 87.5 78 -10.00 13% Y Y Y

M42 Westbound


Obs. Time (s)

Difference (s)

% DifferenceModel

Within 15%

Model Within 1

minValidated

M42 - A441 (N) 77 72 -5.50 8% Y Y Y

M42 - Services 45.9 79 33.10 -42% N Y Y

M42 - A441 (S) 85 36 -49.50 139% N Y Y

100%


Appendix E Traffic Count Data

Key *PCU FLOWS Car 1

LGV 1.5Bus 2

M5 Junction 4 HGV 2.32006 AM Peak (0800-0900)

Movement Car LGV Car/LGV TOTAL OGV1 OGV2 HGV PSV PCU1 155 43 198 16 7 23 0 2722 276 61 337 35 14 49 0 4803 0 0 0 0 0 0 0 04 67 23 90 9 7 16 0 1385 0 0 0 2 0 2 1 76 195 13 208 4 4 8 0 2337 108 21 129 5 2 7 0 1568 197 43 240 37 1 38 2 3539 502 77 579 29 32 61 1 76010 0 0 0 0 0 0 0 011 398 72 470 34 18 52 0 62612 0 0 0 0 0 0 0 013 293 24 317 12 9 21 2 38114 22 5 27 1 1 2 0 3415 0 0 0 0 0 0 0 016 101 11 112 1 0 1 0 12017 145 35 180 21 4 25 1 25718 511 45 556 26 5 31 2 65419 236 26 262 7 7 14 3 31320 0 0 0 0 0 0 0 021 190 21 211 9 8 17 8 27722 249 43 292 12 3 15 0 34823 119 19 138 7 8 15 0 18224 125 30 155 6 4 10 0 19325 0 0 0 0 0 0 0 0


M5 Junction 42006 PM Peak (1700-1800)



M42 Junction 12006 AM Peak (0800-0900)



M42 Junction 22006 AM Peak (0800-0900)


E to D slip 114 11 125 8 16 24 0 186




E to D slip 118 19 137 7 14 21 0 195

longbridge local model validation report issued2 · consistency. this report is an outcome of this...

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