IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v372y2006i1p132-141.html
   My bibliography  Save this article

Modelling of self-driven particles: Foraging ants and pedestrians

Author

Listed:
  • Nishinari, Katsuhiro
  • Sugawara, Ken
  • Kazama, Toshiya
  • Schadschneider, Andreas
  • Chowdhury, Debashish

Abstract

Models for the behavior of ants and pedestrians are studied in a unified way in this paper. Each ant follows pheromone put by preceding ants, hence creating a trail on the ground, while pedestrians also try to follow others in a crowd for efficient and safe walking. These following behaviors are incorporated in our stochastic models by using only local update rules for computational efficiency. It is demonstrated that the ant trail model shows a unusual non-monotonic dependence of the average speed of the ants on their density, which can be well analyzed by the zero-range process. We also show that this anomalous behavior is clearly observed in an experiment of multiple robots. Next, the relation between the ant trail model and the floor field model for studying evacuation dynamics of pedestrians is discussed. The latter is regarded as a two-dimensional generalization of the ant trail model, where the pheromone is replaced by footprints. It is shown from simulations that small perturbations to pedestrians will sometimes avoid congestion and hence allow safe evacuation.

Suggested Citation

  • Nishinari, Katsuhiro & Sugawara, Ken & Kazama, Toshiya & Schadschneider, Andreas & Chowdhury, Debashish, 2006. "Modelling of self-driven particles: Foraging ants and pedestrians," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 372(1), pages 132-141.
    • Handle: RePEc:eee:phsmap:v:372:y:2006:i:1:p:132-141
    DOI: 10.1016/j.physa.2006.05.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437106005917
    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.2006.05.016?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chraibi, Mohcine & Ensslen, Tim & Gottschalk, Hanno & Saadi, Mohamed & Seyfried, Armin, 2016. "Assessment of models for pedestrian dynamics with functional principal component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 475-489.
    2. Zheng, Yaochen & Chen, Jianqiao & Wei, Junhong & Guo, Xiwei, 2012. "Modeling of pedestrian evacuation based on the particle swarm optimization algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4225-4233.
    3. Qiu, Guo & Song, Rui & He, Shiwei & Yin, Weichuan, 2018. "The pedestrian flow characteristics of Y-shaped channel," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 199-212.
    4. Shang, Hua-Yan & Huang, Hai-Jun & Zhang, Yi-Ming, 2015. "An extended mobile lattice gas model allowing pedestrian step size variable," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 283-293.
    5. Shiwakoti, Nirajan & Sarvi, Majid & Rose, Geoff & Burd, Martin, 2011. "Animal dynamics based approach for modeling pedestrian crowd egress under panic conditions," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1433-1449.

    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:372:y:2006:i:1:p:132-141. 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.