IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v643y2024ics0378437124003029.html
   My bibliography  Save this article

A hierarchy of the optimal velocity model with optimal path for pedestrian evacuation: From microscopic to macroscopic models

Author

Listed:
  • Makmul, J.

Abstract

We study the evacuation process of pedestrians by adopting an optimal velocity model. The Eikonal equation is coupled to the optimal velocity model for optimal path to guide the movement directions of pedestrians. It depends on pedestrian density. We derive the corresponding mean field equation, hydrodynamic and scalar models from the scaled microscopic optimal velocity model. Several numerical experiments are performed in a corridor with two exits. We show and compare results on the microscopic as well as on the hydrodynamic and scalar models. Results from microscopic model are closed to the hydrodynamic and scalar models when a large number of particles are considered in microscopic simulation. The computation time increases as number of particles in microscopic simulation increases. The computation times of the hydrodynamic and scalar models are less than the computation time of the microscopic model with large number of particles. Hence it is beneficial to apply the hydrodynamic and scalar models over the microscopic model when a large number of particles in microscopic system are considered.

Suggested Citation

  • Makmul, J., 2024. "A hierarchy of the optimal velocity model with optimal path for pedestrian evacuation: From microscopic to macroscopic models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
  • Handle: RePEc:eee:phsmap:v:643:y:2024:i:c:s0378437124003029
    DOI: 10.1016/j.physa.2024.129793
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124003029
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2024.129793?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.

    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:eee:phsmap:v:643:y:2024:i:c:s0378437124003029. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.