South East Wales Transport Model

Mode-destination model estimation

by James Fox, Bhanu Patruni

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Research Questions

  1. How well do mode-destination models estimated from data collected in the West Midlands predict individual-level behaviour in the South East Wales context?
  2. How well do the transferred models validate in the South East Wales context? In particular, how well do they replicate observed aggregate travel behaviour and what are the sensitivities of the models to changes in travel times and costs?

This report documents the development of the mode-destination (MD) models that form part of the South East Wales Transport Model (SEWTM). The South East Wales mode-destination models were developed by transferring the mode-destination models developed for the PRISM West Midlands model (PRISM) to South East Wales. Local South East Wales data collected by the Welsh Government as part of a Personalised Travel Planning (PTP) project were used to support this methodology.

The report describes the PRISM MD models and presents the transfer methodology, setting out the theory underlying the approach and illustrating how it has been implemented to allow the PRISM models to be transferred to the South East Wales context.

The inputs to the model transfer are described. These are the PTP data from which observed mode-destination choice information has been taken, level-of-service and monetary cost information that has been supplied from the 2015 highway and public transport (PT) networks and attraction data used to represent the attractiveness of destination zones.

The model specifications are documented, detailing both the PRISM model specifications that provided the starting point for the model transfer, as well as the adjustments that have been made to the models so that they are applicable to the South East Wales context.

The key model results presented are the scales obtained for each model transfer that provide a measure of the fit of the PRISM models in the South East Wales context. To validate the models, implied values-of-time, elasticities and trip length distributions have been analysed.

Key Findings

How well did the mode-destination models transfer to the South East Wales context?

  • Overall the transfer process worked well. For four of the home-based purposes the transfer parameter was close enough to one to be fixed to one implying that the mode-destination models have the same explanatory power in the West Midlands and South East Wales contexts. For three of the purposes scale parameters significantly lower than one were identified but the lowest of these was 0.6. For non-home-based purposes, two of the scale parameters were 0.5 and 0.4, and the rest of the parameters were fixed to one.

How well do the models replicate observed travel behaviour in South East Wales?

  • The ability of the models to reproduce the mode shares observed in the local household interview data was assessed. This analysis demonstrated a close match between observed and predicted mode shares for each model purpose.

How do the model sensitivities compare to WebTAG realism test guidance?

  • The sensitivities of the models to fuel cost changes are low relative to the WebTAG guidance, with an overall kilometrage elasticity of -0.17 compared to the -0.25 to -0.35 WebTAG range. The car time elasticities are all consistent with WebTAG guidance as are all but two of the public transport fare elasticity values (these two purposes account for less than 2% of public transport trips).
  • These elasticities were calculated from the unweighted model estimation sample as a check that the demand models respond reasonably to changes in costs and times. Definitive elasticity values can be calculated from base year runs of the model implementation which will be based on estimates of the whole population and will take account of congestion impacts.

Recommendation

  • When any future household interview data is collected full destination information should be collected if possible. We would recommend that a minimum of 4,000 household interviews be collected to provide a representative evidence base for model estimation and in particular an improved ability to take account of variation in cost sensitivity across South East Wales.

Table of Contents

  • Chapter One

    Introduction

  • Chapter Two

    Modelling assumptions

  • Chapter Three

    Spatial transfer approach

  • Chapter Four

    Input data

  • Chapter Five

    Model specification

  • Chapter Six

    Model results

  • Chapter Seven

    Summary and recommendations

  • Appendix A

    Tour building analysis

  • Appendix B

    Ward coding in PTP survey

  • Appendix C

    Public transport level of service data

  • Appendix D

    West Midlands model parameters

  • Appendix E

    Transfer model parameters

Research conducted by

The research described in this report was prepared for the Welsh Government and conducted by RAND Europe.

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