IDEAS home Printed from https://ideas.repec.org/a/jas/jasssj/2022-93-2.html
   My bibliography  Save this article

An Agent-Based Simulation Model of Pedestrian Evacuation Based on Bayesian Nash Equilibrium

Author

Abstract

This research incorporates Bayesian game theory into pedestrian evacuation in an agent-based model. Three pedestrian behaviours were compared: Random Follow, Shortest Route and Bayesian Nash Equilibrium (BNE), as well as combinations of these. The results showed that BNE pedestrians were able to evacuate more quickly as they predict congestion levels in their next step and adjust their directions to avoid congestion, closely matching the behaviours of evacuating pedestrians in reality. A series of simulation experiments were conducted to evaluate whether and how BNE affects pedestrian evacuation procedures. The results showed that: 1) BNE has a large impact on reducing evacuation time; 2) BNE pedestrians displayed more intelligent and efficient evacuating behaviours; 3) As the proportion of BNE users rises, average evacuation time decreases, and average comfort level increases. A detailed description of the model and relevant experimental results is provided in this paper. Several limitations as well as further works are also identified.

Suggested Citation

  • Yiyu Wang & Jiaqi Ge & Alexis Comber, 2023. "An Agent-Based Simulation Model of Pedestrian Evacuation Based on Bayesian Nash Equilibrium," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 26(3), pages 1-6.
    • Handle: RePEc:jas:jasssj:2022-93-2
    as

    Download full text from publisher

    File URL: https://www.jasss.org/26/3/6/6.pdf
    Download Restriction: no
    ---><---

    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:jas:jasssj:2022-93-2. 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: Francesco Renzini (email available below). General contact details of provider: .

    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.