IDEAS home Printed from https://ideas.repec.org/a/taf/transp/v48y2025i1p185-204.html
   My bibliography  Save this article

System capacity model and algorithm for urban multimodal transport network with transfer

Author

Listed:
  • Fang Zhao
  • Bingfeng Si
  • Guanghui Su
  • Tianwei Lu
  • Jose J. Ramasco

Abstract

This paper proposes a method for calculating transport networks capacity in dealing with multimodal transfers. Multimodal networks are represented by a modified ‘supernetwork’, while the passenger’s travels are defined as ‘superpaths’. Within this framework, the relation between the travel demand from O-D matrices and the resulting link flows in the supernetwork is modelled as a relationship matrix to describe urban mobility by using a logit-based stochastic user equilibrium. Based on this relationship matrix, an approximate iteration algorithm (AIA) is developed. Our numerical results show that the AIA performs better than the sensitivity analysis-based algorithm (SAB) and genetic algorithm (GA) regarding the execution-time, and that the capacity of multimodal transport networks can be underestimated if the combined travels are neglected.

Suggested Citation

  • Fang Zhao & Bingfeng Si & Guanghui Su & Tianwei Lu & Jose J. Ramasco, 2025. "System capacity model and algorithm for urban multimodal transport network with transfer," Transportation Planning and Technology, Taylor & Francis Journals, vol. 48(1), pages 185-204, January.
    • Handle: RePEc:taf:transp:v:48:y:2025:i:1:p:185-204
    DOI: 10.1080/03081060.2024.2338185
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03081060.2024.2338185
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03081060.2024.2338185?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:transp:v:48:y:2025:i:1:p:185-204. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/GTPT20 .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.