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Mind the map! The impact of transit maps on path choice in public transit

  • Guo, Zhan
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    This paper investigates the impact of schematic transit maps on passengers' travel decisions. It does two things: First, it proposes an analysis framework that defines four types of information delivered from a transit map: distortion, restoration, codification, and cognition. It then considers the potential impact of this information on three types of travel decisions: location, mode, and path choices.1 Second, it conducts an empirical analysis to explore the impact of the famous London tube map on passengers' path choice in the London Underground (LUL). Using data collected by LUL from 1998 to 2005, the paper develops a path choice model and compares the influence between the distorted tube map (map distance) and reality (travel time) on passengers' path choice behavior. Results show that the elasticity of the map distance is twice that of the travel time, which suggests that passengers often trust the tube map more than their own travel experience on deciding the "best" travel path. This is true even for the most experienced passengers using the system. The codification of transfer connections on the tube map, either as a simple dot or as an extended link, could affect passengers' transfer decisions. The implications to transit operation and planning, such as trip assignments, overcrowding mitigation, and the deployment of Advanced Transit Information System (ATIS), are also discussed.

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

    Volume (Year): 45 (2011)
    Issue (Month): 7 (August)
    Pages: 625-639

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    Handle: RePEc:eee:transa:v:45:y:2011:i:7:p:625-639
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    1. Eran Ben-Elia & Ido Erev & Yoram Shiftan, 2008. "The combined effect of information and experience on drivers’ route-choice behavior," Transportation, Springer, vol. 35(2), pages 165-177, March.
    2. Raveau, Sebastián & Muñoz, Juan Carlos & de Grange, Louis, 2011. "A topological route choice model for metro," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 138-147, February.
    3. Andrew Mondschein & Evelyn Blumenberg & Brian Taylor, 2010. "Accessibility and Cognition: The Effect of Transport Mode on Spatial Knowledge," Urban Studies, Urban Studies Journal Limited, vol. 47(4), pages 845-866, April.
    4. T. Arentze & H. Timmermans, 2005. "Representing mental maps and cognitive learning in micro-simulation models of activity-travel choice dynamics," Transportation, Springer, vol. 32(4), pages 321-340, 07.
    5. Guo, Zhan & Wilson, Nigel H.M., 2011. "Assessing the cost of transfer inconvenience in public transport systems: A case study of the London Underground," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 91-104, February.
    6. Emmerink, Richard H. M. & Nijkamp, Peter & Rietveld, Piet & Van Ommeren, Jos N., 1996. "Variable message signs and radio traffic information: An integrated empirical analysis of drivers' route choice behaviour," Transportation Research Part A: Policy and Practice, Elsevier, vol. 30(2), pages 135-153, March.
    7. Ben-Elia, Eran & Shiftan, Yoram, 2010. "Which road do I take? A learning-based model of route-choice behavior with real-time information," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(4), pages 249-264, May.
    8. Erel Avineri & Joseph Prashker, 2006. "The Impact of Travel Time Information on Travelers’ Learning under Uncertainty," Transportation, Springer, vol. 33(4), pages 393-408, 07.
    9. Golledge, Reginald G., 1995. "Path Selection and Route Preference in Human Navigation: A Progress Report," University of California Transportation Center, Working Papers qt9jn5r27v, University of California Transportation Center.
    10. Caspar Chorus & Theo Arentze & Harry Timmermans, 2007. "Information impact on quality of multimodal travel choices: conceptualizations and empirical analyses," Transportation, Springer, vol. 34(6), pages 625-645, November.
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