PRISM 2006 Model Rebasing Local Model Validation Report

Transcription

1 CEPOG Core Support Team CENTRO, Centro House 16 Summer Lane Birmingham B19 3SD PRISM West Midlands PRISM 2006 Model Rebasing Local Model Validation Report November 2009 Canterbury House, 85 Newhall Street, Birmingham, B3 1LZ, United Kingdom Tel: +44 (0) ; Fax: +44 (0)

2 PRISM Model Rebasing Issue and Revision Record Rev Date Originator Checker Approver Description A 07/01/09 MS PO TVV Draft Report 1 D 04/11/09 MB/MO/ NB/SK LC PO Draft Report for BB3-MM only This document has been prepared for the titled project or named part thereof and should not be relied upon or used for any other project without an independent check being carried out as to its suitability and prior written authority of Mott MacDonald being obtained. Mott MacDonald accepts no responsibility or liability for the consequence of this document being used for a purpose other than the purposes for which it was commissioned. Any person using or relying on the document for such other purpose agrees, and will by such use or reliance be taken to confirm his agreement to indemnify Mott MacDonald for all loss or damage resulting therefrom. Mott MacDonald accepts no responsibility or liability for this document to any party other than the person by whom it was commissioned.

3 Executive Summary 4 1. Introduction 1 BACKGROUND 1 CONTEXT 1 KEY MODEL SPECIFICATION ISSUES 3 Modelling Software 3 Temporal Scope 3 Planning Data 3 Improving the Highway Network Model 3 Developing a New Public Transport Network 3 Stages in Model Development 4 Spatial Detail 4 SCOPE OF THE REPORT 4 2. Background to Policy Responsive Integrated Strategy Model (PRISM v2.0) 8 INTRODUCTION 8 HISTORY 8 ZONING SYSTEM 8 MODEL SYSTEM 9 MODELLED TIME PERIODS 11 UPDATE TASKS Data Sources 12 INTRODUCTION 12 EMPLOYMENT DATA 12 Comparison with TEMPRO data 14 HOUSEHOLD INCOME DATA 14 POPULATION DATA 15 Comparison of the ONS Population Data with the RSS and TEMPRO Forecasts 16 HOUSEHOLDS 19 Comparison with the TEMPRO 5.4 Data 19 SCHOOL ENROLMENTS Network Development 22 INTRODUCTION 22 UPDATING THE HIGHWAY NETWORK 22 HIGHWAY NETWORK CODING CHECKING PROCEDURE 23

4 PUBLIC TRANSPORT NETWORKS 24 Methodology 24 BUILDING the PUBLIC TRANSPORT NETWORK 25 Transferring the Rail Network and Timetables from the Reference Case Network 25 Estimation of AM and IP headways for rail services 25 Transferring the Coventry Bus Routes from the PRISM Network 25 Estimation of AM and IP headways for Coventry Bus Services 25 Coding the Intermediate/External Bus Lines Matrix Development 28 INTRODUCTION 28 OBTAINING THE 2006 PRIOR MATRICES for modes with variable demand 29 OBTAINING THE 2006 PRIOR MATRICES for modes with FIXED demand 30 LGV and HGV Trip Matrices 30 Motorway Through-Trip (MTT) Matrices 30 HGV Through-Trip (HTT) Matrices 30 Rail Through-Trip Matrices 31 CHECKING THE INITIAL FORECASTS Highway Model Calibration 33 INTRODUCTION 33 MATRIX ESTIMATION Highway Model Validation 41 INDEPENDENT COUNT VALIDATION (NON-MOTORWAY) 41 MOTORWAY COUNT VALIDATION 45 JOURNEY TIME VALIDATION Public Transport Model Calibration/Validation 48 INTRODUCTION 48 ACCEPTABILITY CRITERIA 48 OBSERVED MATRICES 48 MERGING PROCESS 48 OBSERVED COUNTS 49 ASSIGNMENT PARAMETERS 50 PUBLIC TRANSPORT MODEL CALIBRATION RESULTS 50 Train 50 Metro 51 Bus Summary 58

5 Executive Summary This report documents the results of the rebasing of the West Midlands Policy Response Strategic Model (PRISM) from 2001 to This task was been recognised as an urgent need by all parties involved, underpinned by the Department for Transport advice note recommending that the observed trip information used in a traffic model should not be more than six years old. 1.1 The PRISM model covers both the highway and public transport systems in the West Midlands linked to a disaggregate demand model. The latter models a variety of travel behaviour, including; car ownership, PT travel pass ownership, tour frequency, destination choice, mode choice and time of day choice. PRISM s primary study area is the former West Midlands County, also referred to as the metropolitan area, which is comprised of the following seven metropolitan districts: Birmingham Coventry Dudley Sandwell Solihull Walsall Wolverhampton The PRISM models four time periods: AM peak period (07:00-09:30), covering both highway and public transport networks; Inter-peak period (09:30-15:30), covering both highway and public transport networks; PM peak period (15:30-19:00), covering the highway network only; and Off peak period (19:00-07:00), this also covers the highway network only. The PRISM matrix development built on the success of the 2001 matrices by either forecasting to 2006 or applying growth factors to the 2001 data. These methods ensured that the robustness of the PRISM 2001 matrices was carried forward to the 2006 base. PRISM networks were also updated to incorporate schemes built between 2001 and The PRISM model was calibrated and validated to a good standard, with the public transport model meeting nearly all of its counts. This model can be used with confidence to forecast the strategic effects of proposed highway improvements and public transport schemes. The new version of PRISM is referred to as v3.0.

6 1. Introduction BACKGROUND 1.1 This Local Model Validation Report (LMVR) has been prepared by Mott MacDonald as part of the commission to provide consultancy support to the West Midlands metropolitan districts, CENTRO and the Highways Agency. 1.2 The work carried out involved updating the existing Policy Responsive Integrated Strategic Model (PRISM) from its 2001 base year to a 2006 base and showing that its level of validation is sufficient for application. 1.3 The overall aim of PRISM is to facilitate the forecast testing and assessment of alternative land use options and highway infrastructure proposals. 1.4 This LMVR describes the overall modelling approach undertaken before describing the update process and the validation results. CONTEXT 1.5 PRISM consists of a detailed network model covering the highway and public transport (PT) systems, which is linked to a disaggregate demand model. The latter models a variety of travel behaviour, including; car ownership, PT travel pass ownership, tour frequency, destination choice, mode choice and time of day choice. PRISM s primary study area is the former West Midlands County, also referred to as the metropolitan area, which is comprised of the following seven metropolitan districts: Birmingham; Coventry; Dudley; Sandwell; Solihull; Walsall; and Wolverhampton. The coverage of the model is illustrated in Figure Page 1 of 64

7 1.6 The level of detail in the highway and public transport networks is highest in the primary or core study area (the West Midlands Metropolitan Area). A second area, called the intermediate area, has a similar coverage of highway and public transport networks, but contains less detail in junction coding and the zoning system is coarser. This intermediate area roughly covers the home-to-work area of the metropolitan districts, governed by trip making observed in the 2001 Census. Travel response behaviour has the same level of detail as in the core area. For the rest of the West Midlands Region, the network coverage and the zoning system are coarser and as a result, link loadings do not fully reflect local conditions. Outside the West Midlands Region the networks are skeletal, zones cover large areas and link loadings are only partial. Figure Study Area of PRISM Intermediate Core WM Region Motorway A-Road Page 2 of 64

8 KEY MODEL SPECIFICATION ISSUES Modelling Software 1.7 The highway and public transport models for PRISM have been updated from the current version, v2.0, which uses VISUM 9.4, to VISUM Temporal Scope 1.8 PRISM models four time periods: Planning Data AM peak period (07:00-09:30), covering both highway and public transport networks; Inter-peak period (09:30-15:30), covering both highway and public transport networks; PM peak period (15:30-19:00), covering the highway network only; and Off peak period (19:00-07:00), this also covers the highway network only. 1.9 The following sources were used to obtain planning data for 2006 Employment estimates from Annual Business Inquiry (ABI); Income estimates from CACI; Population data from Office of National Statistics (ONS); Household numbers from Annual Monitoring Reports (AMR); Number of pupils in West Midlands from EduBase (register of all educational establishments in England and Wales, maintained by the Department for Children, Schools and Families); and Number of students in higher education institutions for 2005/2006 from the Higher Education Statistics Agency (HESA). Improving the Highway Network Model 1.10 The original PRISM highway model was validated to a 2001 base year. PRISM v3.0 has been updated to the 2006 base year to meet the Design Manual for Roads and Bridges (DMRB) guidelines The Birmingham City Centre Model (BCCM) network was the starting point for the network update. BCCM contains detailed information in the Birmingham City Centre area, along with changes to the PRISM network between 2001 and The zoning system and network detail in the Birmingham City Centre was adjusted to match the requirements of PRISM Bus lanes have been coded in the revised highway networks using information provided by CENTRO for the seven metropolitan districts in the West Midlands to reflect a reduction in link capacities. Developing a New Public Transport Network 1.13 A new 2006 public transport model network has been developed for V3.0 using CENTRO network data (links, nodes, stops) along with the following additional tasks: Centroid connectors for the PRISM zoning system were redefined; Page 3 of 64

9 Intermediate and external bus services were coded (the existing CENTRO network does not include these services); Coventry bus services were reviewed and updated using timetables from the website as the CENTRO network only covers Birmingham, the Black Country and Solihull; and New rail services were coded The CENTRO model has been updated and calibrated based on 2005 autumn timetable information. Stages in Model Development 1.15 As shown in Figure 1.2, the 2006 planning data, along with the updated networks and preliminary skims are fed into the travel demand Model to create initial 2006 base matrices. These initial matrices are then assigned to the updated networks and used in the calibration and validation process. The final 2006 base matrices are an output from the calibration/validation process. Synthetic 2006 base matrices are estimated from the costs resulting from assigning the base matrices and the 2006 planning data. Spatial Detail 1.16 WebTAG emphasises that the size of zones in the highway assignment process is critical. They need to be sufficiently small to enable accurate routing to be predicted, yet sufficiently large to enable travel demand to and from the zone to be estimated with confidence. The same is true for the public transport assignment, with an additional requirement being to provide sufficient definition around key stops and stations In 2001, the PRISM model study area was divided into 898 zones and the same zoning has been retained in version 3.0. The zoning system consists of four distinct areas, with decreasing levels of detail, including: the West Midlands County, an intermediate area, the rest of the West Midlands Region and the rest of Great Britain (see Figure 1.1). All zones are compatible with ward boundaries. Figure 1.3 shows the PRISM zoning in the core area and Figure 1.4 shows the PRISM zoning in the core and intermediate areas We are confident that the sizes of the zones in PRISM allow for sufficient land use and geographical disaggregation hence the accurate representation of trip movements at a strategic level within the West Midlands area. SCOPE OF THE REPORT 1.19 This LMVR consists of nine chapters. Chapter Two describes version 2 of the PRISM model. Chapter Three gives the details of the data collected for updating the model. Chapter Four describes how the networks were developed whilst Chapter Five describes the development of the demand matrices. Chapter Six outlines the highway model calibration results while Chapter Seven describes the highway model validation results. Chapter Eight contains the results of the public transport model calibration. A summary is given in Chapter Nine A number of Appendices are attached to the report to provide supplementary information, including details of the highway model calibration, highway model validation and public transport model calibration. Page 4 of 64

10 Figure 1.2 Stages in Model Development 1. Up-to-date 2006 Planning Data Population Land use 4. Initial 2006 Base Matrices Population Model Year Updating Networks HW: Identify schemes Coding projects in 2004 networks (BCCM (*) ) Coding bus lanes PT: 2006 Timetables Reroute services 3. Preliminary Skims Preliminary Matrices Freight, MTT, RTT Matrices Assignment Preliminary Matrices Calculation of Annual Growth Rates Travel Demand Models Skim Processing (HW, PT) 2006 Matrices Final Processing P Calibration/Validation 2006 Base Matrices Highway Public Transport Assignment Initial 2006 Base Year Matrices New Initial 2006 PT Matrices Observed matrices (CENTRO) Observed counts (Point census data) Matrix Correction Assignment Initial 2006 Base Year Matrices Matrix Validation Matrix Correction Observed counts (CENTRO) Matrix Validation CarD B 2006 B 2006 HGV, LGV PT B Estimation 2006 Base Synthetic Matrices Skim Processing (HW, PT) Travel Demand Models Final Processing S 2006 (*) Base year highway networks taken from the Birmingham City Centre Model (BCCM) were used to develop the 2006 networks. BCCM networks have 2004 as their base year. Page 5 of 64

11 Figure 1.3 PRISM Zoning in the Study Core Area Page 6 of 64

12 Figure 1.4 PRISM Zoning in the Study Core Area and in the Intermediate Area

13 2. Background to Policy Responsive Integrated Strategy Model (PRISM v2.0) INTRODUCTION 2.1 PRISM is a disaggregate multi-modal transport model, developed between 2002 and The fundamental disaggregation is in the use of individual (disaggregate) records from the home and roadside interviews to estimate the demand responses, in order to maximise the amount of information available for modelling. PRISM utilises the disaggregation of demand responses, demand segments, networks and zoning structure. HISTORY 2.2 In the mid-nineties a strategic model was developed for the West Midlands, the West Midlands Strategic Transport Model (WMSTM), which has been used to support the Local Transport Plan and, ultimately, the West Midlands Area Multi-Modal Study (WMAMMS). The model had a number of recognised weaknesses: The response mechanisms were based on aggregate, zonal data, which led to unrealistically slow changes to policy and investment; The zonal definition was coarse, with only 100 zones covering the West Midlands metropolitan area; Junctions were not explicitly coded, which led to a likely underestimate of future road congestion; and The software on which the model was based (EMME/2) was not very user-friendly which limited application to a few professionals. 2.3 This led to a desire to develop a new, state-of-the-art, strategic transport model, which was more suited to the policies to be assessed in the 21st Century. The data collection exercises carried out by CEPOG and the Highways Agency in 2001 and the West Midlands Transport Survey 2001 (WMTS 2001), to support the Local Transport Plan, provided a good opportunity to build this new model, as data is usually the most expensive component of such an exercise. The data sources used were: ZONING SYSTEM 2001 West Midland Local Authorities roadside interview data (JDT RSI); 2001 Highway Agency motorway roadside interview data (HA RSI); 2001 West Midland household interview data (2001 HHI) and Birmingham Travel Survey data (BTS HHI); 2001 car park survey data (CP); 2001 MDS freight data (MDS); 2001 airport survey data (BAX); and 2001 motorway through trip data (MTT) obtained from ANPR cameras. 2.4 The West Midlands conurbation interacts with the rest of the region, and with the rest of the country. The transport networks in the West Midlands do not just serve local and regional traffic, but also national traffic flows, for example on the motorways, some of the A-roads and on the rail network. The model network therefore covers the whole of the country to some degree. 2.5 However, the focus of the model is on the residents of the conurbation, as: Page 8 of 64

14 They are the largest users of transport facilities in the area; and They will be most affected by and responsive to alternative transport infrastructure and planning scenarios. 2.6 This focus on local residents, with recognition of regional and national transport flows is common to many transport models and is dealt with by a reducing the level of detail in the representation of population and transport networks in areas more remote from the West Midlands conurbation. The model has been divided into nearly 900 zones (spatial segments), differentiating between internal, intermediate and external zones. 574 zones are internal to the West Midlands conurbation, and data on population, employment and schools has been collected for these. For the seven metropolitan authorities this implies an average of three zones per electoral ward, increasing in the denser parts of Birmingham to about five zones per ward. All travel modes and demand responses are covered. The PRISM zones generally follow the boundaries of 2001 Census Output Areas; 286 zones are in the rest of the region. These are subdivided into an intermediate area, in which all demand responses are covered to the same extent as within the metropolitan area, and the rest where travel demand does not respond to policy (just re-routing in the network model). The highway and rail networks are comprehensive, but only bus routes that have one of their end points within the metropolitan area are represented; The rest of the country is covered by about 30 zones, which inevitably are large. The model does not reflect any responses to local policy for these areas as: a) the model does not represent the full demand for travel from those zones; b) the model has no representation of all alternative modes and destinations that exist for travellers from those areas, and c) travellers over long distances are less likely to be affected by local policy or network improvements. 2.7 The zoning system is as shown in Figures 1.3 and 1.4. MODEL SYSTEM 2.8 The PRISM model consists of a number of components that interact: The network model; The demand or response model; and The output and analysis modules. 2.9 The implementation of these components is complex, and is illustrated in Figure The network model is the most visible component of the system. It represents all relevant transport modes in the West Midlands and calculates flows and travel times and speeds, referred to in PRISM as levels-ofservice (LOS) The demand model reflects the most important travel responses to policy or investment. In reality, such responses will be complex and interrelated; within the model this has been dealt with by separating different responses, and iterating between them. Page 9 of 64

15 Figure PRISM Model System 2.12 The responses distinguished are (at the household or personal level): Car ownership (whether or not to purchase one or more cars); Tour frequency (how many trips to make during the day); Destination choice (where to travel to carry out daily activities such as work, shopping, education); Mode choice (which of the available modes to use); Time of day choice (at which time to make each trip, given levels of congestion, but also possible future pricing regimes); and Public transport pass ownership (as this affects the cost of using public transport as an alternative) The output from the demand model is a series of trip matrices that contain the demand for travel between discrete spatial segments (zones) for the different modes for the different time periods modelled. These are an essential input to the network models and hence a natural conduit between the two components Any changes in route chosen by travellers are calculated by the network models, which also output any changes in travel times or costs resulting from the travel responses in the demand model. Because these time and cost changes affect the decisions made by travellers a feedback loop is required, and the model is applied iteratively until a stable solution has been found - this equilibration may be compared with the day-to-day learning process that travellers would go through. Page 10 of 64

16 2.15 A separate access model has been set up for Birmingham International Airport. The airport model calculates, for externally given growth figures in passengers to and from the airport, where they would come from and which mode they would use. The model applies only to passengers and visitors, as the workers at the airport are governed by the standard home-to-work element of the model. MODELLED TIME PERIODS 2.16 As the levels of service differ across the day, either because of congestion on the highway; peak/off peak fares payable for public transport; or the service frequencies for public transport, the model distinguishes between the four time periods explained in Paragraph The demand model operates at the 24 hour level; the base year distribution of trips across the day taken from the household interviews. Because of the time-of-day choice model the distribution may change in future scenarios, for example due to increasing congestion or time-dependent charging policies. UPDATE TASKS 2.18 The update of PRISM from version 2.0 to version 3.0 involves updating and rebasing the 2001 highway and transport models to The update tasks include: Reflecting junction improvements made since 2001 in the highway model; Updating bus routes and frequencies (to reflect the situation in 2006); Collecting and processing 2006 planning data; Updating networks to 2006 using the new VISUM version 10.0; Obtaining preliminary skims from the 2006 networks; Obtaining initial 2006 base matrices; Estimating 2006 freight trips, motorway and rail through-trip matrices; Calibrating and validating the PRISM model using 2006 count and journey time data; and Estimating 2006 base synthetic matrices. Page 11 of 64

17 3. Data Sources INTRODUCTION 3.1 For the development of PRISM v3.0, the following planning data for 2006 were used: Employment estimates from Annual Business Inquiry (ABI); Income estimates from CACI; Population data from Office of National Statistics (ONS); Household numbers from Annual Monitoring Reports (AMR); Number of pupils in West Midlands from EduBase (register of all educational establishments in England and Wales, maintained by the Department for Children, Schools and Families); and Number of students in higher education institutions for 2005/2006 from the Higher Education Statistics Agency (HESA). 3.2 Together with the network data (e.g. network skim costs), the planning data information was fed into the demand model to estimate the synthetic future trip matrices. 3.3 The rest of this chapter explains the methodology adopted and the data sources used to generate the updated planning inputs to the model and provides a summary analysis. Appendix A contains details of the method adopted for PRISM re-basing. EMPLOYMENT DATA 3.4 From the Annual Business Inquiry (ABI), the employment data was available for 2006 at the Lower-layer Super Output Area (LSOA) level. This information was extracted from both the Nomis system (which is a source of official labour market statistics) and from the ONS source (via a Chancellor of Exchequer's Notice licence) and subsequently allocated to PRISM zones. 3.5 The ABI source is based on a sample of workplace employment, which excludes the self-employed, HM Forces, manual home-workers, domestic staff in private households and people under 16 years of age. 3.6 Table 3.2 shows the summary of 2006 employment data for districts, Shires and for the entire region. These are compared to 2001 Census data. Between 2001 and 2006, the number of jobs increased for the service sector. The largest increase took place in Herefordshire (24.6%) for the service sector and in Sandwell (63.3%) for other sectors. On the other hand, in the same period, the number of jobs in the manufacturing sector decreased, with the largest drop in Coventry (-44.6%). The big drop in manufacturing seems to have been compensated by a big increase in other jobs. Overall, between 2001 and 2006, the number of jobs increased, with the largest increase shown in Herefordshire (16.5%). Page 12 of 64

18 Table Comparison of 2001 and 2006 Employment Data PLANNING DATA: Employment Service Manufacturing Other Retail Total Districs & Shires Growth Growth Growth Growth Growth Birmingham 375, , % 84,630 55, % 17,530 18, % 63,450 67, % 477, , % Coventry 103, , % 32,230 17, % 4,350 5, % 19,850 21, % 140, , % Dudley 89,070 90, % 28,240 19, % 7,320 7, % 20,970 20, % 124, , % Sandwell 81,840 89, % 38,580 27, % 5,300 8, % 16,300 14, % 125, , % Solihull 69,670 82, % 15,440 10, % 6,580 10, % 13,950 15, % 91, , % Walsall 67,180 79, % 31,230 22, % 4,760 4, % 15,610 14, % 103, , % Wolverhampton 74,520 83, % 23,410 14, % 9,510 13, % 16,070 15, % 107, , % Worcestershire 169, , % 47,154 40, % 10,514 11, % 43,403 40, % 226, , % Shropshire 80,617 85, % 15,185 13, % 7,544 7, % 19,613 20, % 103, , % Staffordshire 220, , % 68,737 51, % 16,821 19, % 54,039 57, % 305, , % Warwickshire 161, , % 41,860 31, % 12,170 15, % 33,720 38, % 215, , % Wrekin 51,056 60, % 22,281 17, % 2,420 2, % 10,231 11, % 75,708 80, % Herefordshire 43,237 53, % 12,844 11, % 3,843 4, % 10,877 13, % 59,782 69, % Stoke-on-Trent 73,748 82, % 34,046 17, % 5,371 5, % 18,627 18, % 113, , % Met Area 861, , % 253, , % 55,350 68, % 166, , % 1,169,980 1,174, % Rest of Region 800, , % 242, , % 58,685 66, % 190, , % 1,100,175 1,166, % West Midlands Region 1,661,134 1,855, % 495, , % 114, , % 356, , % 2,270,155 2,340, % Source: Annual Business Inquiry (ABI) for 2005 and This data has been extracted from the Nomis system (official labour market statistics) and ONS via a licence (Chancellor of Exchequer's Notice). Note: Retail is included in Services. Page 13 of 64

19 Comparison with TEMPRO data 3.7 Table 3.3 shows the comparison between the ABI employment data that was used in this study with the TEMPRO 5.4 figures for the year Table Comparison of the ABI and the TEMPRO Employment Data for 2006 PLANNING DATA: Employment Total Districs & Shires ABI 2006 TEMPRO-2006 Dif. % Birmingham 471, , % Coventry 139, , % Dudley 116, , % Sandwell 126, , % Solihull 102, , % Walsall 106, , % Wolverhampton 111, , % Worcestershire 234, , % Shropshire 107, , % Staffordshire 323, , % Warwickshire 245, , % Wrekin 80,607 88, % Herefordshire 69,635 86, % Stoke-on-Trent 105, , % Met Area 1,174,567 1,256, % Rest of Region 1,166,089 1,307, % West Midlands Region 2,340,656 2,564, % Sources: Annual Business Inquiry (ABI) for 2006 and TEMPRO 5.4 Forecasts. 3.8 Some of the differences in employment between ABI and TEMPRO will be due to the inclusion of selfemployed people in the TEMPRO database whereas the ABI source does not. From the 2001 Census, 7.4% of people aged are self-employed 1. The difference between the ABI and TEMPRO totals for the West Midlands is 8.7% of the TEMPRO total. Therefore, we are confident that this difference is due to the exclusion of self-employed people in TEMPRO. 3.9 The employment data input to PRISM is used in a singly constrained distribution model, and so their distribution is more important than their absolute values. HOUSEHOLD INCOME DATA 3.10 The experimental ONS dataset 2 for at the Middle-layer Super Output Area (MSOA) level was first considered as the source for household income data. However, deflation of this household income 1 Census 2001: Table KS09a Economic Activity, West Midlands. 2 The methodology used to produce the SOA estimates for mid-2002 onwards is subject to further development. In view of this ongoing work the mid-2001 to mid-2006 SOA estimates were published as experimental statistics. Any 'experimental' data produced by ONS are NOT fully accredited as a National Statistic. Page 14 of 64

20 data to 2001 prices 3 showed a decline in real average household income between 2001 and 2006, which is inconsistent with the expected increase Rather than use the experimental ONS dataset, it was decided to make use of the CACI information provided by DfT for the Transport Innovations Fund (TIF) work. Table 3.4 shows a summary of the 2006 income figures extracted from CACI, by districts, shires and the entire region. The 2006 incomes have been deflated using the Treasury figures and are compared to the 2001 base year to determine income growth between 2001 and Table Comparison of 2001 and 2006 Average Household Income PLANNING DATA: Household Income (from CACI) Districts and Shires Deflated Growth Birmingham 22,992 28,429 24, % Coventry 24,600 31,656 27, % Dudley 24,122 29,693 25, % Sandwell 20,516 26,082 22, % Solihull 29,804 34,549 30, % Walsall 22,454 28,384 24, % Wolverhampton 21,252 27,260 23, % Worcestershire 28,898 34,310 29, % Shropshire 28,073 34,123 29, % Staffordshire 27,175 33,712 29, % Warwickshire 29,148 35,439 30, % Telford and Wrekin 25,975 32,566 28, % WM county 23,370 29,088 25, % Black Country 22,092 27,853 24, % PRISM wide 24,888 30,735 26, % Source: CACI. Note: The 2006 incomes (from CACI) have been deflated to 2001 prices, using GDP deflator table from the website The comparison between household income data for 2006 (deflated to 2001) shows an increase in real average household income for all the districts and shires, which is consistent with the expected increase. The average growth from 2001 to 2006 for the entire region (7.9%) is nearly half of the growth estimated for the ten year period between 2001 and 2011 (14.7%). POPULATION DATA 3.13 The population data encompasses the total number of people living in each of the PRISM zones in the West Midlands Region and the surrounding intermediate areas, i.e. 830 zones in total. This includes estimates of the population living in households in each zone as well as those living in different institutions such as education or health. 3 Using Treasury figures Page 15 of 64

21 3.14 The population data was obtained using the ONS experimental population datasets for the mid-year 2006, at the Lower and Middle-layer SOAs. This data was then allocated to the PRISM zones Table 3.5 shows a summary of population data by gender and age group for all districts, shires and the entire region. The 2006 figures are compared to the 2001 base year data From 2001 to 2006, the largest growth was for male population in the Birmingham area (6.1%) and the least growth was in Wolverhampton (0.4%) for female population. When considering population by age band, the largest growth was for the band aged in Birmingham (8.4%) and for the same band, Shropshire had the highest fall in population (-5.8%). Considering population for all age groups and genders, again Birmingham had the largest growth (4.8%) and Dudley had the least growth (0.9%). Comparison of the ONS Population Data with the RSS and TEMPRO Forecasts 3.17 Tables 3.5 and 3.6 show comparisons of the mid-year ONS population data with the RSS and TEMPRO 5.4 forecasts for the year 2006 by districts and shires in the West Midlands County The RSS forecasts are less than the ONS figures for age band 0-19 and are higher for age-band and these two datasets are almost the same for age band The differences between these data sources are almost negligible when looking at all age-bands combined together Looking at the differences between the ONS figures and the TEMPRO 5.4 forecasts, it is evident that in the majority of cases, the TEMPRO figures are lower than the ONS forecasts. In particular, for age-band 0-64, the largest difference is in Birmingham (-3.3%) and the lowest difference is in Wolverhampton (- 0.1%). The corresponding figures for age band 65 years and above are in Birmingham (-6.6%) and Walsall (-1.1%). For all age groups, the pattern is similar to age band 0-64, i.e. the largest difference is in Birmingham (-3.7%) and the lowest difference is in Walsall (0.2%). Page 16 of 64

22 Table Comparison of 2001 and 2006 Population Data PLANNING DATA: Population Male Female T 0-19 T T T 65+ Total Districs & Shires Growth Growth Growth Growth Growth Growth Growth Birmingham 465, , % 495, , % 282, , % 343, , % 194, , % 140, , % 960,609 1,006, % Coventry 145, , % 148, , % 79,213 81, % 106, , % 62,832 65, % 45,300 45, % 293, , % Dudley 148, , % 154, , % 74,122 76, % 100,998 96, % 76,867 78, % 50,396 53, % 302, , % Sandwell 135, , % 145, , % 75,189 78, % 96,748 98, % 62,641 64, % 46,185 45, % 280, , % Solihull 96,039 98, % 102, , % 51,019 52, % 62,327 61, % 51,466 53, % 33,367 35, % 198, , % Walsall 122, , % 129, , % 67,164 69, % 83,357 80, % 60,129 61, % 40,687 43, % 251, , % Wolverhampton 114, , % 118, , % 60,785 61, % 80,667 80, % 52,154 54, % 39,462 39, % 233, , % Warwickshire 245, , % 254, , % 120, , % 168, , % 130, , % 80,773 87, % 499, , % Shropshire 19,645 20, % 19,446 20, % 8,823 8, % 12,335 11, % 11,043 11, % 6,890 7, % 39,091 40, % Staffordshire 203, , % 209, , % 103, , % 139, , % 109, , % 60,070 68, % 412, , % Worcestershire 207, , % 215, , % 103, , % 142, , % 112, , % 66,042 72, % 423, , % Wrekin 67,518 69, % 70,214 72, % 38,602 40, % 50,312 48, % 32,558 35, % 16,260 18, % 137, , % WM County 1,226,524 1,277, % 1,293,198 1,322, % 689, , % 873, , % 560, , % 395, , % 2,519,722 2,600, % Intermediate 743, , % 769, , % 374, , % 513, , % 395, , % 230, , % 1,512,921 1,570, % Total 1,970,232 2,052, % 2,062,411 2,118, % 1,064,416 1,105, % 1,387,017 1,404, % 955,594 1,003, % 625, , % 4,032,643 4,170, % Source: Experimental ONS datasets for mid-year Note: Total = WM County+ Intermediate Area. Table Comparison of ONS Population Data with RSS Forecasts PLANNING DATA: Population T 0-19 T T T 65+ Total Districs & Shires 2006 RSS-2006 Dif. % 2006 RSS-2006 Dif. % 2006 RSS-2006 Dif. % 2006 RSS-2006 Dif. % 2006 RSS-2006 Dif. % Birmingham 294, , % 372, , % 201, , % 137, , % 1,006,510 1,006, % Coventry 81,277 78, % 113, , % 65,973 65, % 45,656 45, % 306, , % Dudley 76,940 74, % 96,806 99, % 78,185 78, % 53,333 53, % 305, , % Sandwell 78,139 75, % 98, , % 64,819 64, % 45,999 46, % 287, , % Solihull 52,822 51, % 61,169 62, % 53,736 53, % 35,221 35, % 202, , % Walsall 69,512 67, % 80,804 83, % 61,133 61, % 43,093 43, % 254, , % Wolverhampton 61,627 59, % 80,670 82, % 54,338 54, % 39,984 40, % 236, , % WM County 714, , % 904, , % 580, , % 400, , % 2,600,081 2,600, % Sources: Experimental ONS datasets for mid-year 2006 and RSS Forecasts (October 2007) Page 17 of 64

23 Table Comparison of ONS Population Data with TEMPRO Forecasts PLANNING DATA: Population T 0-64 T 65+ Total Districs & Shires 2006 TEMPRO-2006 Dif. % 2006 TEMPRO-2006 Dif. % 2006 TEMPRO-2006 Dif. % Birmingham 869, , % 137, , % 1,006, , % Coventry 260, , % 45,656 43, % 306, , % Dudley 251, , % 53,333 51, % 305, , % Sandwell 241, , % 45,999 44, % 287, , % Solihull 167, , % 35,221 33, % 202, , % Walsall 211, , % 43,093 42, % 254, , % Wolverhampton 196, , % 39,984 38, % 236, , % WM County 2,199,385 2,157, % 400, , % 2,600,081 2,540, % Sources: Experimental ONS datasets for mid-year 2006 and TEMPRO 5.4 Forecasts Page 18 of 64

24 HOUSEHOLDS 3.20 Information on the number of households is available from the Department for Communities and Local Government (DCLG) 2004-based projections for households at local authority district level. This data includes the 2006 data, but no information is available on household characteristics at local authority district level (e.g. single person, lone parent, couples, etc.). In addition, household projections between 2001 and 2011 at local authority district level can be obtained from the Chelmer Projection Model For the purpose of this study, the total number of households for 2006 was derived from the Annual Monitoring Reports (AMR) generated by different districts in the West Midlands Region. These AMRs provide the total number of households that were completed and demolished between 2001 and 2007 at the aggregate district wide level for each of the West Midlands districts. In addition, Mott MacDonald maintains a database which holds a single site return relating to the specific location of household completions in the region. This data was used to identify the number of household completions at the PRISM zone level for the required years. It should be noted that this information is available for every year between 2001 and 2007 for the metropolitan areas in the West Midlands, but this source is not available for all shire authorities for the year 2005 onwards. To overcome this shortcoming, all the available household data were allocated to the PRISM zones and for the missing data, the aggregate level AMR completion numbers were used as an overall control. Comparison with the TEMPRO 5.4 Data 3.22 Table 3.8 shows a comparison of the 2006 household information used in the model with that from the TEMPRO 5.4 data source for the West Midlands metropolitan area The differences between these sources are small, with the largest difference in Walsall (TEMPRO figure is 3% higher than the model) and the smallest difference is in Birmingham (0%). For the West Midlands County as a whole, the difference between these sources is only 0.8%. Table Comparison of Household Data between the Model and the TEMPRO Forecasts PLANNING DATA: Households Total Districs & Shires 2006 TEMPRO-2006 Dif. % Birmingham 400, , % Coventry 124, , % Dudley 126, , % Sandwell 118, , % Solihull 83,632 83, % Walsall 102, , % Wolverhampton 99, , % WM County 1,055,136 1,063, % SCHOOL ENROLMENTS 3.24 School enrolment data is an input to the population model and contains the total number of students enrolling at schools in each of the PRISM zones in the West Midlands County and the intermediate surrounding area. This data contains the following information: PRISM zone number; Number of school enrolments in primary schools per zone; Page 19 of 64

25 Number of school enrolments in secondary schools per zone; Number of school enrolments in further education (i.e. Sixth Form colleges and College places) per zone ; and Number of school enrolments in higher (tertiary) education per zone For 2006, the following information was obtained: The number of pupils in each school in the West Midlands Government Office Region (primary and secondary schools), including independent schools. This data was purchased from Edubase 4. The number of students in each of the higher education institutions for the year 2005/2006 (i.e. the academic year between 1 August 2005 and 31 July 2006). This data was obtained from the Higher Education Statistics Agency s website: Using information on school locations (including the post code) extracted from the Edubase data source and higher education establishment locations obtained from the relevant website of institutions, together with the above information, this data was allocated to the PRISM zones It should be noted that the Edubase data does not contain information on the number of pupils in the 16+ establishments. In order to overcome this shortcoming, the proportion of the total number of school enrolments in further education (16-18) for the year 2001 was assumed to remain the same in the year Table 3.9 shows a summary of educational enrolments in 2006 compared to the 2001 base year by districts, shires and regions. The total growth for the WM region for primary and further education is in line with the growth of 0-19 year olds from Table EduBase is a register of all educational establishments in England and Wales, maintained by the Department for Children, Schools and Families. 5 HESA - Higher Education Statistics Agency. Page 20 of 64

26 Table Comparison of 2001 and 2006 Educational Enrolments PLANNING DATA: School Enrolments Primary Secondary Further Higher Total Districs & Shires Growth Growth Growth Growth Growth Birmingham 94, , % 75,394 73, % 10,259 10, % 59,330 69, % 239, , % Coventry 29,280 28, % 23,558 22, % 2,654 2, % 41,075 49, % 96, , % Dudley 31,263 27, % 21,208 20, % 5,013 5, % 57,484 52, % Sandwell 28,819 28, % 19,542 18, % 1,493 1, % 49,854 48, % Solihull 18,805 20, % 18,771 17, % 2,853 2, % 40,429 40, % Walsall 25,063 26, % 22,162 19, % 1,637 1, % 48,862 47, % Wolverhampton 21,967 22, % 17,194 19, % 1,451 1, % 20,930 24, % 61,542 67, % Warwickshire 36,513 42, % 37,313 36, % 4,796 4, % 78,622 84, % Shropshire 20,522 23, % 20,954 19, % 2,511 2, % 43,987 45, % Staffordshire 66,360 65, % 60,391 62, % 5,566 5, % 10,200 12, % 142, , % Worcestershire 30,997 35, % 34,143 35, % 4,404 4, % 6,530 7, % 76,074 83, % Wrekin 13,097 14, % 12,247 11, % 1,335 1, % 1,785 3, % 28,464 31, % Herefordshire 13,903 13, % 10,967 10, % 1,390 1, % 26,260 26, % Stoke-on-Trent 21,279 20, % 15,274 14, % 2,709 2, % 18,310 15, % 57,572 52, % Met Area 250, , % 197, , % 25,360 26, % 121, , % 594, , % Rest of Region 202, , % 191, , % 22,711 23, % 36,825 39, % 453, , % West Midlands Region 452, , % 389, , % 48,071 49, % 158, , % 1,048,166 1,089, % Sources: EduBase; Page 21 of 64

27 Team PRISM Joint Application 4. Network Development INTRODUCTION 4.1 In the 2006 model rebasing exercise, the model network was updated and extended. 4.2 The assignment platform for the PRISM model was changed from VISUM 9.4 to the most recent version VISUM Version 10 was the latest version of VISUM and there were a number of updates which were valuable to PRISM applications, including: New and improved graphical parameters with a simplified and easy to use graphical user interface. Better interfaces with detailed modelling tools such as VISSIM. UPDATING THE HIGHWAY NETWORK 4.3 As a starting point, the Birmingham City Centre Model (BCCM) networks were used. The networks have a 2004 base year and are more detailed in the Birmingham City Centre area. They also incorporate network changes to represent the M6 Toll and include changes to the road network between 2001 and For the purpose of this work, the network detail in the Birmingham City Centre was reduced and the zoning system was aggregated to match the PRISM zoning system. 4.4 The networks were transferred from a VISUM 9 platform to a VISUM 10 platform. The transfer of highway networks and the assignment in VISUM 10 was tested (using a sample network from BCCM) and accepted. Network and matrix elements were successfully transferred. A reduction in assignment runtime was observed. Table 4.1 shows a comparison of sector flows following assignments in VISUM 9 and VISUM 10, considered to be sufficiently close. Table Sector Analysis Summary Sector Direction VISUM 9 VISUM 10 V10/V9% 1 in % 1 out % 2 in % 2 out % 3 in % 3 out % 4 in % 4 out % 5 in % 5 out % all % Tables 4.3 and 4.4 show comparisons of VISUM 9 and 10 data from RSI and independent count sites. It is evident that the migration from VISUM 9 to VISUM 10 will have little effect on the overall results. Appendix B contains detailed assignment results from the transfer of the model networks from VISUM 9 to VISUM Page 22 of 64

28 Team PRISM Joint Application Table RSI Summary RSI Summary No. Counts No. with GEH<5 % with GEH<5 VISUM 9 VISUM % 76% Table Independent Count Summary Independent Counts VISUM 9 VISUM 10 Link Types No. of Counts Within Validation Criteria % Within Within Validation Criteria % Within Motorways % 63 77% D'Cways % 83 57% Rural-roads % 18 60% A-roads % % B-roads % % U-roads % % Total % % 4.5 It was also necessary to incorporate new bus lanes introduced since 2001 on the networks, as the presence of bus lanes reduces the overall link capacity. To assist in this task, CENTRO provided the required information for the seven districts, comprising Birmingham, Coventry, Dudley, Sandwell, Solihull, Walsall and Wolverhampton. 4.6 In order to avoid inconsistencies resulting from the migration to VISUM 10 testing, and due to findings from the HA s projects elsewhere, a detailed check of highway network coding was carried out. Upon the completion of checks, final logic checks of the network were undertaken using assignment methodology. HIGHWAY NETWORK CODING CHECKING PROCEDURE 4.7 A detailed check of highway network coding was carried out to identify and correct any inconsistencies. This was done in two stages: motorway checks; and other checks. (i) Motorway Checks: Checks were carried out on the following motorways and their junctions: M5; M6; M6 Toll; M54; and M42. The checks consisted of: i) Links: Link type and number of lanes: Comparing the motorway link type 6 to online virtual map resources (best information available as no additional data was collected). 6 Motorway link type is related to the number of lanes that the motorway link has and associated speed flow curves. Page 23 of 64

29 Team PRISM Joint Application ii) iii) Nodes: Node capacities; Lane definitions; Signalised junctions: Checking whether signalised junctions timings have been allocated to the junctions or if any of the priority junctions have been changed to signalised junctions. Turning Relations: Type of movement: Checking whether the coding was appropriate (for example, whether it was a left turn or a right turn); Turning capacity and delays: If a new signalised junction had been introduced, information on the turning capacities was checked. (ii) Non Motorway Checks: i) Links: Bus lane: Bus lane information was added to the networks, using the data provided by CENTRO. Link type, capacity and number of lanes were reduced if bus lanes were introduced; Link type and number of lanes: Checks were carried out by comparing the PRISM network to online virtual map resources. ii) iii) iv) Nodes: Node capacities; Lane definitions; Signalised junctions: Checking whether signalised junctions timings were allocated to the junctions or any of the priority junctions had been changed to signalised junctions. Turning Relations: Type of movement: Checking whether it was coded appropriately (for example, whether it was a left turn or a right turn); Turning capacity and delays: If a new signalised junction was introduced, this information was calculated based on turning capacities. Zone Connectors: Checking whether there was a need to reallocate the zone connectors or there was a need to add more connectors to represent the zone. This was carried out by checking the demographic layout of the individual zone and assessing whether there was a need to make any changes. PUBLIC TRANSPORT NETWORKS Methodology 4.8 A new PRISM Public Transport network was built by adopting the existing CENTRO bus network and replacing the zoning system with the PRISM zoning system to allow for its integration with the PRISM demand model. This was then merged with the PRISM train and metro reference case networks (PRISM v2.0), which cover a wider area than the CENTRO rail networks. 4.9 The following additional tasks were undertaken: The connectors for the PRISM zoning system were rebuilt; Page 24 of 64

30 Team PRISM Joint Application Intermediate/external bus lines were coded because the CENTRO network did not include them; The complete Coventry PRISM PT network (including bus) was merged into the CENTRO network because the CENTRO network only covers the Birmingham, Black Country and Solihull areas. BUILDING THE PUBLIC TRANSPORT NETWORK Transferring the Rail Network and Timetables from the Reference Case Network 4.10 The reference case (PRISM v2.0) rail networks and timetables (train and metro) were merged with the CENTRO bus network. As part of this task, the rail links, stops, lines and timetables were imported, following which the walk links in the merged network were updated The PRISM reference case year is 2001 and so all services where changes had occurred since 2001 were updated. Estimation of AM and IP headways for rail services 4.12 AM and IP headways were estimated from the timetable information. A partial service was included for all those that depart before 07:00 (10:00 for IP) and run in the West Midlands region during the AM (IP) period. The station of departure for such services was considered to be the first station called at after 07:00 (10:00). Transferring the Coventry Bus Routes from the PRISM Network 4.13 The CENTRO PT network does not include the Coventry area, therefore the Coventry bus services were transferred from the PRISM reference case network into the new PRISM PT network. Figures 4.1 and 4.2 illustrate the CENTRO bus network and the new PRISM bus network including all the Coventry bus services, respectively. Estimation of AM and IP headways for Coventry Bus Services 4.14 This task was carried out using the information from Coding the Intermediate/External Bus Lines 4.15 The CENTRO network does not cover the PRISM intermediate area; these services were taken from the PRISM reference case. Additional data was taken from bus timetable information on the internet for shire authorities in the West Midlands Region. This data was used to obtain details of all the bus stops, and AM and IP headways in the intermediate area AM and IP headways for intermediate/external bus lines were estimated using the data available on bus timetables. Figure 4.3 shows the new PRISM bus network including all the intermediate/external bus services. Page 25 of 64

31 Team PRISM Joint Application Figure 4.1 The CENTRO Bus Network Figure 4.2 The New PRISM Bus Network (Including Coventry Bus Services) Page 26 of 64

32 Team PRISM Joint Application Figure 4.3 The New PRISM Bus Network including all the intermediate/external bus services Replacing the CENTRO Zoning System with the PRISM Zoning System and Rebuilding the Zone Connectors 4.17 This task involved replacing the CENTRO zoning system with the PRISM zoning system to allow its integration with the PRISM demand model The zone connectors were first coded for the West Midlands County areas (i.e. Birmingham, Coventry, Dudley, Sandwell, Solihull, Walsall and Wolverhampton) and then were coded for the intermediate and external areas. The maximum lengths of zone connectors used are as follows: Bus kilometres Metro kilometres Train kilometre 4.19 For the purpose of calibration of rail and metro, a short walk link was created to connect the station node and the zone connectors. The walk links contain passenger count data (boarding and alighting) to be used in the calibration process. Page 27 of 64

33 Team PRISM Joint Application 5. Matrix Development INTRODUCTION 5.1 The modes with variable demand within the PRISM model are: car, for the following purposes: business, commute, education and others; bus; metro; and train. 5.2 The modes with non-variable (fixed) demand, i.e. that are not passed iteratively between the supply and demand models, are as follows: light goods vehicles (LGV) and heavy goods vehicles (HGV); motorway through traffic for HGV (HTT); motorway through traffic for three of the four car purposes 7 (Car MTT); and rail through trips (RTT). 5.3 The PRISM supply model assigns a fixed level of demand for the modes listed in paragraph The process to develop the matrices for the variable demand modes (paragraph 5.1) was broken down into the following steps: 2006 planning data along with preliminary network costs were fed into the PRISM demand model to obtain synthetic matrices for forecast matrices called prior matrices were obtained by pivoting the 2001 base matrices with the synthetic matrices for 2001 and Matrix estimation was carried out on the prior matrices to obtain the final 2006 base matrices. 5.5 For the fixed demand modes (paragraph 5.2), the 2006 prior matrices were obtained from either interpolating between 2001 data and 2011 forecasts, or by applying growth rates. The prior matrices were then subjected to matrix estimation to obtain the final 2006 matrices. 7 Car MTT is disaggregated into three purposes: business, commute, and other. 8 Validated observed matrices and synthetic matrices for 2001 exist from PRISM v2. Page 28 of 64

34 Team PRISM Joint Application OBTAINING THE 2006 PRIOR MATRICES FOR MODES WITH VARIABLE DEMAND 5.6 The modes with variable demand are so-called because their trip and costs matrices are passed iteratively between the supply and demand models. The cost and trip matrices vary between iterations with the variation 9 getting successively smaller. Once this variation is small enough, the model is considered to have converged. 5.7 PRISM forecast matrices are the result of a process called pivoting. The mathematical principle of pivoting is shown in Figure 5.1 and involves multiplying the observed base matrix by the growth forecast by the demand model, thus maintaining the overall structure of the base matrices. Figure 5.1: The Mathematical Principle of Pivoting P Where: P forecast forecast = B base year S S forecast base year is the forecast year matrix Bbase year is the observed base year matrix S forecast is the synthetic forecast year matrix Sbase year is the synthetic base year matrix 5.8 The 2006 prior matrices were forecast from a 2001 base. Using Figure 5.1 it can be seen that the growth S 2006 forecast by the demand model is represented by the entity 10 which multiplies the observed 2001 S2001 base matrix on a cell-wise basis. 5.9 The 2001 synthetic matrices remain unchanged from PRISM v2. In order to obtain the 2006 synthetic matrices, the 2006 planning data along with preliminary skims were fed through the demand model The preliminary highway skims were obtained by assigning the following demand to the updated highway network: Car demand estimated as part of the WMEDB work 11. For the non-car highway modes including MTT, the prior matrices were assigned (see the following section - Obtaining the 2006 Prior Matrices for Modes with Fixed Demand) The preliminary PT skims were taken from the networks developed during the TIF work The measure of demand/supply convergence is the %GAP formula. See WebTAG Unit , Paragraph Convergence : for more information. 10 This is the ratio of the synthetic 2006 matrix to the synthetic 2001 matrix. 11 As part of the West Midlands Emissions Database work, 2006 car demand had been estimated by performing matrix estimation on the 2001 matrices using a selection of 2006 counts. Page 29 of 64

35 Team PRISM Joint Application OBTAINING THE 2006 PRIOR MATRICES FOR MODES WITH FIXED DEMAND LGV and HGV Trip Matrices LGV and HGV matrices were derived by applying sector-wise growth rates to the PRISM v2.0 (2001) matrices. The growth rates were obtained from the GBFM4.0 runs for its 2001 base year and 2011 forecast year. The matrices were used as an input to the calibration process and were also used to skim the preliminary 2006 cost matrices from the highway network. Motorway Through-Trip (MTT) Matrices 5.13 The MTT matrices used in the matrix estimation process were the forecast 2011 matrices as used in PRISM V2. These were preferred over an interpolation between 2001 and 2011 because the M6 Toll was not in operation in 2001, and hence an interpolation would not reflect the 2006 situation in which the M6 Toll exists An interpolation between 2001 and 2011 was used to obtain the preliminary skims (see paragraph 5.10). Using the 2011 matrices would have resulted in unrealistic preliminary costs. HGV Through-Trip (HTT) Matrices 5.15 After assigning the HGV matrices, the model showed no HGV presence on the M6 Toll, contrary to observed counts. A new demand segment (HTT) was created to address this HTT represents long distance freight trips that are assumed to have higher values of time (for example transporting high value or perishable goods). Prior matrices representing these trips were created through select link analyses on the M6 Toll for MTT business car users. The OD distribution of high value of time HGVs was assumed to be the same as that for business car users. These matrices were then factored back to observed HGV counts on the M6 Toll Values of time were estimated for HTT, so that after assignment the M6 Toll flows would match closely the observed values. An acceptable value was found to be halfway between HGV VOT and Car Business VOT Sensitivity tests were carried out using the updated AM network to check how HTT trips would respond to alternative toll charges, the results of which are sensible and are summarised in Table The updated 2006 PT networks were not fully developed at the time the prior matrices were forecast. The networks developed during the TIF work were taken as the most up to date networks available. Page 30 of 64

36 Team PRISM Joint Application Table Toll Charge Sensitivity Tests Full Toll Direction Modelled HGV HGV_TT Total Observed Eastbound Westbound % discount Direction Modelled HGV HGV_TT Total Observed Eastbound Westbound Double charge Direction Modelled HGV HGV_TT Total Observed Eastbound Westbound Rail Through-Trip Matrices 5.19 The growth rate for rail through-trip matrices (RTT) was obtained from two documents, the National Rail Trends Yearbook for and for This growth rate, of 20.8% was applied to the 2001 RTT matrices to derive the 2006 RTT matrices. CHECKING THE INITIAL FORECASTS 5.20 The 2006 prior matrices were then assigned into the updated highway and PT networks, and a base year validation check was carried out to establish the robustness of the initial forecasts. The results are shown in Table The initial forecast for growth of car traffic between 2001 and 2006 is close to the observed figure of 6%, while the initial PT forecasts lie in the range of observed values. This suggests that the initial forecasts are sensible Table 5.2 compares the growth of vehicle kilometrage for the period between observed values and the initial forecast. The model forecasts a growth of 11% compared with an observed 7% growth; i.e. a lengthening of average trip length. This value is considered reasonable for an initial forecast. Page 31 of 64

37 Team PRISM Joint Application Table 5.1 Comparison between Observed and Modelled Traffic Growth Source Car Train Metro* Bus Coverage Transport Trend 07 TSGB 2007 Rail: National and Light Rail 13% 32% 9% Bus and Ligh rail: England -8% Bus: English Metropolitan Area 6% 28% Great Britain 2% WM metro only Road Traffic Stats % National Road CENTRO: General Monitoring % 8% -8% West Midlands National Rail Trend Year Book % West Midlands Regional Transport Statistics 2007: Chapter 2 32% 9% England -4% -12% West Midlands 2006 Rebasing 5% 24% 0% 0% PRISM Table Comparisons of Observed and Modelled Vehicle-Km Growth Source Car Coverage Transport Trend 07 7% Great Britain Road Traffic Stats % National Road Regional Transport Statistics 2007: Chapter 4 7% West Midlands 2006 Rebasing 11% PRISM Page 32 of 64

38 Team PRISM Joint Application 6. Highway Model Calibration INTRODUCTION 6.1 Highway matrix estimation was undertaken at the following levels for different time periods: Roadside interview sectors; Roadside interview screenlines; Roadside interview counts; City/Town Centre cordons; Intermediate cordons and screenlines; and Motorways. 6.2 DMRB acceptability guidelines were adopted for the calibration process, as seen in Table 6.1. Table 6.1 DMRB Acceptability Guidelines Criteria and Measure Acceptability Guideline Assigned hourly flows compared with observed flows 1. Individual flows within 15% for flows vph 2. Individual flows within 100 vph for flows < 700 vph 3. Individual flows within 400 vph for flows > 2700 vph 4. T otal s creenline flows (normally > 5 links) to be within 5% 5. Observed and modelled cordon flows should be within 5% 6. GE H statistic i. Individual flows: G E H<5 ii. S creenline (+) totals : G E H<4 Modelled journey times compared with observed times 7. Times within 15% (or 1 minute, if higher) > 85% of cases > 95% of cases > 85% of cases All (or nearly all) screenline > 85% of routes 6.3 The GEH statistic referred to in the table is the generally accepted value used as an indicator of goodness of fit, i.e. the extent to which the modelled flows match the corresponding observed flows. The GEH is defined as: Error! Objects cannot be created from editing field codes., where M = modelled flow and C = observed flow. 6.4 Sector calibration was carried out by comparing the total number of trips crossing the individual cordons in the inbound and outbound directions. The boundary of the sectors was defined using the RSI screenlines which divide the West Midlands County into five geographical areas, as shown in Figure The results of the calibration using RSI screenlines, as shown in Figure 6.1, can be found in Appendix C. 6.6 The locations of the RSI counts can be seen in Figure 6.2. The summary of the RSI count level calibration results can be found in Appendix C. Page 33 of 64

39 Team PRISM Joint Application 6.7 The following nine city/town centre cordons were identified and used for matrix estimation: Birmingham City Centre; Coventry City Centre; Dudley Town Centre; Merry Hill Shopping Centre; West Bromwich Town Centre; Solihull Town Centre; Sutton Coldfield Town Centre; Walsall Town Centre; and Wolverhampton City Centre. 6.8 Figure 6.3 shows the location of the City/Town centre cordons in the West Midlands County. The City/Town Centre level calibration results can be found in Appendix C. 6.9 Intermediate cordons and screenlines were used to improve the model calibration in parts of the network further away from the RSI and internal cordons. Figure 6.4 shows the location of the selected intermediate cordons and screenlines. The calibration results can be found in Appendix C Figure 6.5 shows the location of motorway count sites. The motorway calibration results can be found in Appendix C. Page 34 of 64

40 Figure 6.1 Roadside Interview Sectors / Screenlines Based on Ordnance Survey mapping with permission of the Controller of HMSO Crown copyright. Unauthorised reproduction infringes Crown copyright and may lead to prosecution or civil proceedings. Mott MacDonald Licence number PRISM Calibration Screenlines Page 35 of 64

41 Figure 6.2 RSI Counts Page 36 of 64

42 Figure 6.3 City/Town Centre Cordons Page 37 of 64

43 Figure Intermediate Cordons and Screenlines Page 38 of 64

44 Figure Motorway Counts Page 39 of 64

45 MATRIX ESTIMATION 6.11 Matrix estimation methods were used to adjust a given OD matrix in such a way that the result of their assignment closely matches observed data. The matrix estimation tool used as part of the calibration process of PRISM V3.0 is called TFlowFuzzy The initial matrices developed as in chapter 5 were loaded into the updated 2006 networks along with the observed data outlined above A summary of the changes to the OD matrices as a result of matrix estimation is as follows: At the sector level, adjustments were minimal for the following modes across all time periods: Car- Business; Car-Commute; Car-Education; and Car-Others. The greatest change in peak period trip total was less than 1% for Car-Education in OP. The total number of peak hour GV trips increased by 13% after matrix estimation. The total number of peak hour MTT trips decreased by 34% after matrix estimation. This can be attributed to the use of 2011 forecast matrices as the initial matrices which have 2011 levels of traffic rather than The distribution of trip lengths was preserved to an acceptable level. Page 40 of 64

46 7. Highway Model Validation 7.1 The PRISM highway validation consisted of checking model performance using: Independent counts; Motorway counts; and Journey time data. 7.2 The DMRB acceptability guidelines as shown in Table 6.1 were adopted for the validation process, using the GEH calculation from paragraph The criterion used for motorway flow validation was as follows: For flows below 1000 vehicles per hour: individual flows within 200 vph For flows between 1000 to 3000 vehicles per hour: individual flows within 20% For flows above 3000 vehicles per hour: individual flows within * [(Obs ) /3000] vph These criteria differ to those in DMRB, and were agreed with the PRISM Management Group (PMG) which included a TAME representative. INDEPENDENT COUNT VALIDATION (NON-MOTORWAY) 7.4 Figure 7.1 shows the location of independent counts used in the highway validation exercise and Table 7.1 provides a summary of the independent count validation, which includes the results for both the flow and GEH criteria. Appendix D shows further details of this analysis. Table Summary of Independent Count Validation C riteria AM IP Flow criteria > 85% of cases 488 out of out of out of out of % 82% 100% 80% GEH < 5 > 85% of cases 510 out of out of out of out of % 84% 98% 85% OP PM 7.5 More than 80% of the independent count locations met the flow criteria across all time periods whilst more than 84% met the GEH criteria. 7.6 Figure 7.2 plots the locations of independent counts for which a GEH of 5 was not met in the AM peak. The locations are not concentrated in any areas so we can be confident of the validation, especially as the number of cases is only 1% less than the required 85%. 7.7 Figure 7.3 plots the locations of independent counts for which the flow criteria was not met in the AM peak. Similar to the locations where the GEH criteria were not met, the locations are spread over the entire region without any concentrations in particular areas giving confidence in the results. The same reasoning applies to locations in the IP and PM peak where the flow criteria haven t been met. Details of all counts can be found in Appendix D. Page 41 of 64

47 Figure Independent Counts Page 42 of 64

48 Figure 7.2 Locations of Independent Counts for which a GEH of <5 Was Not Attained on Non-Motorway Roads Page 43 of 64

49 Figure 7.3 Locations of Independent Counts for which the Flow Criteria Was Not Attained on Non-Motorway Roads Page 44 of 64

50 MOTORWAY COUNT VALIDATION 7.8 Figure 7.4 shows the location of motorway sites used for the purpose of validation and Table 7.2 provides a summary of the motorway count validation. Appendix D shows further details of this analysis. Table 7.2 Summary of Motorway Count Validation AM IP OP PM No. of counts within criteria Total no. of counts % 87% 85% 93% 87% 7.9 The model met the validation criteria shown in Paragraph 7.3. JOURNEY TIME VALIDATION 7.10 For the validation of modelled journey times in PRISM, several routes were selected which extended across the whole of the highway network in the study area. These routes cut across different screenlines, extending into different sectors to provide comprehensive network coverage and to dampen the effects of any localised junction delay. Figure 7.5 illustrates the routes that were used for the journey time validation of the PRISM highway network. The journey time data was extracted from the C-JAMS 13 online database Table 7.3 provides a summary of journey time validation, which includes the details of both the flow and GEH validation. Appendix D shows further details of this analysis. Table 7.3 Summary of Journey Time Validation C riteria AM IP Times within 15% 33 out of out of out of 48 > 85% of cases (or 1 minute if higher) 69% 79% 83% PM 7.12 The number of routes that met the DMRB validation requirements for journey time validation was 69%, whilst 79% of routes met the criteria in the inter-peak and 83% for the PM peak. Further details can be found in Appendix D. 13 More information on journey time is available from Page 45 of 64

51 Figure Motorway Counts Page 46 of 64

52 Figure Journey Time Validation Routes in PRISM Page 47 of 64