IDEAS home Printed from https://ideas.repec.org/h/spr/lnopch/978-981-96-9697-0_31.html
   My bibliography  Save this book chapter

Risk Prevention and Control Strategies of Large Passenger Flow in Railway Passenger Stations

Author

Listed:
  • Ziqi Zhang

    (Beijing Jiaotong University)

  • Juanqiong Gou

    (Beijing Jiaotong University)

Abstract

With the continuous rise of railroad passenger traffic, the phenomenon of heavy passenger flow has become more and more common in railroad passenger stations, which brings serious challenges to the safe operation of passenger stations. In order to alleviate the unexpected heavy passenger flow events, this paper proposes the risk prevention and control strategy of heavy passenger flow in railroad passenger stations, and establishes the risk prevention and control model by collecting data from different sources, including two major models, namely, risk assessment and early warning model and human-computer collaborative decision-making support model, which combines the risk early warning with the human-computer collaborative decision-making to provide a new perspective for the risk prevention and control of heavy passenger flow in railroad passenger stations, and provides a useful reference for the practical application, and is of great help to improve the quality and safety of railway passenger transportation services. Railroad passenger transportation service quality and safety level has important help.

Suggested Citation

  • Ziqi Zhang & Juanqiong Gou, 2025. "Risk Prevention and Control Strategies of Large Passenger Flow in Railway Passenger Stations," Lecture Notes in Operations Research,, Springer.
  • Handle: RePEc:spr:lnopch:978-981-96-9697-0_31
    DOI: 10.1007/978-981-96-9697-0_31
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:lnopch:978-981-96-9697-0_31. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.