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Assessing the cost of transfer inconvenience in public transport systems: A case study of the London Underground

  • Guo, Zhan
  • Wilson, Nigel H.M.
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    Few studies have adequately assessed the cost of transfers2 in public transport systems, or provided useful guidance on transfer improvements, such as where to invest (which facility), how to invest (which aspect), and how much to invest (quantitative justification of the investment). This paper proposes a new method based on path choice,3 taking into account both the operator's service supply and the customers' subjective perceptions to assess transfer cost and to identify ways to reduce it. This method evaluates different transfer components (e.g., transfer walking, waiting, and penalty) with distinct policy solutions and differentiates between transfer stations and movements. The method is applied to one of the largest and most complex public transport systems in the world, the London Underground (LUL), with a focus on 17 major transfer stations and 303 transfer movements. This study confirms that transfers pose a significant cost to LUL, and that cost is distributed unevenly across stations and across platforms at a station. Transfer stations are perceived very differently by passengers in terms of their overall cost and composition. The case study suggests that a better understanding of transfer behavior and improvements to the transfer experience could significantly benefit public transport systems.

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    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 45 (2011)
    Issue (Month): 2 (February)
    Pages: 91-104

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    Handle: RePEc:eee:transa:v:45:y:2011:i:2:p:91-104
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    1. Liu, Henry X. & Recker, Will & Chen, Anthony, 2004. "Uncovering the contribution of travel time reliability to dynamic route choice using real-time loop data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(6), pages 435-453, July.
    2. Azevedo, JoseAugusto & Santos Costa, Maria Emilia O. & Silvestre Madeira, Joaquim Joao E. R. & Vieira Martins, Ernesto Q., 1993. "An algorithm for the ranking of shortest paths," European Journal of Operational Research, Elsevier, vol. 69(1), pages 97-106, August.
    3. Menghini, G. & Carrasco, N. & Schüssler, N. & Axhausen, K.W., 2010. "Route choice of cyclists in Zurich," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 754-765, November.
    4. Shafahi, Yousef & Khani, Alireza, 2010. "A practical model for transfer optimization in a transit network: Model formulations and solutions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(6), pages 377-389, July.
    5. Hine, J. & Scott, J., 2000. "Seamless, accessible travel: users' views of the public transport journey and interchange," Transport Policy, Elsevier, vol. 7(3), pages 217-226, July.
    6. L. Randall Wray & Stephanie Bell, 2004. "Introduction," Chapters, in: Credit and State Theories of Money, chapter 1 Edward Elgar.
    7. Guihaire, Valérie & Hao, Jin-Kao, 2008. "Transit network design and scheduling: A global review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(10), pages 1251-1273, December.
    8. Bhat, Chandra R. & Pulugurta, Vamsi, 1998. "A comparison of two alternative behavioral choice mechanisms for household auto ownership decisions," Transportation Research Part B: Methodological, Elsevier, vol. 32(1), pages 61-75, January.
    9. Rietveld, P. & Bruinsma, F. R. & van Vuuren, D. J., 2001. "Coping with unreliability in public transport chains: A case study for Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(6), pages 539-559, July.
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