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Rail Passenger Demand Forecasting: Cross-Sectional Models Revisited

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  • Wardman, Mark
  • Lythgoe, William
  • Whelan, Gerard

Abstract

This chapter revisits cross-sectional models of rail travel demand, a much neglected area in recent years, by covering three developments in the context of inter-urban travel. First, the models are extended to allow a detailed analysis of catchment areas; the ticket-sales data that are used to estimate these models only cover journeys between stations. Second, access to and egress from stations are investigated by refining functions of population and accessibility to stations separately from rail service quality. The best models are achieved with inverted s-shaped access and egress functions rather than assuming constant elasticity. Third, station choice is modeled using a multinomial logit model that yields fresh insights into rail travel demand.

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  • Wardman, Mark & Lythgoe, William & Whelan, Gerard, 2007. "Rail Passenger Demand Forecasting: Cross-Sectional Models Revisited," Research in Transportation Economics, Elsevier, vol. 20(1), pages 119-152, January.
    • Handle: RePEc:eee:retrec:v:20:y:2007:i:1:p:119-152
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    1. Mark Wardman & Jonathan Tyler, 2000. "Rail network accessibility and the demand for inter-urban rail travel," Transport Reviews, Taylor & Francis Journals, vol. 20(1), pages 3-24, January.
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    Cited by:

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    2. Robenek, Tomáš & Azadeh, Shadi Sharif & Maknoon, Yousef & de Lapparent, Matthieu & Bierlaire, Michel, 2018. "Train timetable design under elastic passenger demand," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 19-38.
    3. Rahman, Syed & Balijepalli, Chandra, 2016. "Understanding the determinants of demand for public transport: Evidence from suburban rail operations in five divisions of Indian Railways," Transport Policy, Elsevier, vol. 48(C), pages 13-22.
    4. Simon P. Blainey & John Armstrong & Andrew S. J. Smith & John M. Preston, 2016. "New routes on old railways: increasing rail’s mode share within the constraints of the existing railway network," Transportation, Springer, vol. 43(3), pages 425-442, May.
    5. F. Cerina & L. Cocco & K. Mannaro & M. Marchesi & F. Pigliaru, 2020. "Insularity and the development of a local railway network," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(2), pages 683-702, July.
    6. Blainey, Simon, 2010. "Trip end models of local rail demand in England and Wales," Journal of Transport Geography, Elsevier, vol. 18(1), pages 153-165.
    7. Hu, Xinlei & Wang, Xiaokun (Cara) & Ni, Linglin & Shi, Feng, 2022. "The impact of intercity economic complementarity on HSR volume in the context of megalopolization," Journal of Transport Geography, Elsevier, vol. 98(C).
    8. Givoni, Moshe & Rietveld, Piet, 2014. "Do cities deserve more railway stations? The choice of a departure railway station in a multiple-station region," Journal of Transport Geography, Elsevier, vol. 36(C), pages 89-97.
    9. Blainey, Simon P. & Preston, John M., 2013. "A GIS-based appraisal framework for new local railway stations and services," Transport Policy, Elsevier, vol. 25(C), pages 41-51.

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