IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v671y2025ics0378437125003425.html
   My bibliography  Save this article

Experimental study on pedestrian movement when facing an attacker in the presence of obstacles

Author

Listed:
  • Yu, Hang
  • Song, Weiguo
  • Tao, Yixi
  • Li, Xintong
  • Huang, Can
  • Zhang, Jun

Abstract

The objective of research on pedestrian dynamics lies in investigating the characteristics of crowd movement and implementing measures to ensure crowd safety. Pedestrian groups facing an attacker, as a special type of movement group exhibiting unique interaction behaviors, hold significant importance in understanding their movement characteristics. In scenarios where pedestrians must evade an attacker, obstacles can function as tools for mutual evasion, effectively enhancing personnel safety. This paper presents an experimental design focusing on motion interactions between pedestrians and attackers in the presence of obstacles. By adjusting the height of obstacles, the experiment controls visibility between pedestrians and attackers, while obstacle length varies from 1.6 m to 6.4 m in 1.6 m increments. Results demonstrate that when obstacles are present, pedestrians preferentially utilize them and tend to make more effective use of long and low obstacles in their interactions with attackers. Finally, this study delineates crowd motion modeling principles in this experimental scenario—specifically addressing how perceived risk is assessed by crowds when obstructed by high or low obstacles—and investigates exit selection behavior among pedestrians, thus laying groundwork for modeling pedestrian movement in complex scenarios involving an attacker.

Suggested Citation

  • Yu, Hang & Song, Weiguo & Tao, Yixi & Li, Xintong & Huang, Can & Zhang, Jun, 2025. "Experimental study on pedestrian movement when facing an attacker in the presence of obstacles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 671(C).
  • Handle: RePEc:eee:phsmap:v:671:y:2025:i:c:s0378437125003425
    DOI: 10.1016/j.physa.2025.130690
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437125003425
    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.2025.130690?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:671:y:2025:i:c:s0378437125003425. 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.