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Dynamic System Optimal Routing In Multimodal Transit Network

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Author Info

  • Tai-Yu Ma

    ()
    (LET - Laboratoire d'économie des transports - CNRS : UMR5593 - Université Lumière - Lyon II - Ecole Nationale des Travaux Publics de l'Etat)

  • Jean-Patrick Lebacque

    ()
    (IFSTTAR/GRETTIA - Génie des Réseaux de Transport Terrestres et Informatique Avancée - IFSTTAR - Université Paris XII - Paris Est Créteil Val-de-Marne)

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    Abstract

    The system optimal routing problem has been widely studied for road network while it is less considered for public transit system. Traditional shortest-path-based multimodal itinerary guidance systems may deteriorate the system performance when the assigned lines become congested. For this issue, we formulate the dynamic system optimal routing model for multimodal transit system. The transit system is represented by a multilevel graph to explicitly simulate passenger flow and transit system operations. A solution algorithm based on the cross entropy method is proposed, and its performance is compared with the method of successive averages in static and dynamic cases. Numerical study on a simple multimodal transit network provides the basis for comparing the system optimal routing and user optimal routing under different congestion levels.

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    File URL: http://hal.archives-ouvertes.fr/docs/00/74/03/47/PDF/trb2013_Ma_Lebacque_HAL.pdf
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    Bibliographic Info

    Paper provided by HAL in its series Working Papers with number hal-00740347.

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    Date of creation: 26 Jul 2012
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    Handle: RePEc:hal:wpaper:hal-00740347

    Note: View the original document on HAL open archive server: http://hal.archives-ouvertes.fr/hal-00740347
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    Web page: http://hal.archives-ouvertes.fr/

    Related research

    Keywords: system optimal routing; multimodal; transit;

    This paper has been announced in the following NEP Reports:

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    1. Tong, C. O. & Wong, S. C., 2000. "A predictive dynamic traffic assignment model in congested capacity-constrained road networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(8), pages 625-644, November.
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