IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Dynamic System Optimal Routing In Multimodal Transit Network

  • 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)

Registered author(s):

    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.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL: http://hal.archives-ouvertes.fr/docs/00/74/03/47/PDF/trb2013_Ma_Lebacque_HAL.pdf
    Download Restriction: no

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

    as
    in new window

    Length:
    Date of creation: 26 Jul 2012
    Date of revision:
    Handle: RePEc:hal:wpaper:hal-00740347
    Note: View the original document on HAL open archive server: http://hal.archives-ouvertes.fr/hal-00740347
    Contact details of provider: Web page: http://hal.archives-ouvertes.fr/

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as in new window
    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.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:hal:wpaper:hal-00740347. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (CCSD)

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.