IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-319-02447-9_81.html
   My bibliography  Save this book chapter

Stochastic Transition Model for Pedestrian Dynamics

In: Pedestrian and Evacuation Dynamics 2012

Author

Listed:
  • Michael Schultz

    (Technische Universität Dresden, Department of Air Transport Technology and Logistics, Faculty of Transport and Traffic Sciences “Friedrich List”)

Abstract

The proposed stochastic model for pedestrian dynamics is based on existing approaches using cellular automata, combined with substantial extensions, to compensate the deficiencies resulting of the discrete grid structure. This agent motion model is extended by both a grid-based path planning and mid-range agent interaction component. The stochastic model proves its capabilities for a quantitative reproduction of the characteristic shape of the common fundamental diagram of pedestrian dynamics. Moreover, effects of self-organizing behavior are successfully reproduced. The stochastic cellular automata approach is found to be adequate with respect to uncertainties in human motion patterns, a feature previously held by artificial noise terms alone.

Suggested Citation

  • Michael Schultz, 2014. "Stochastic Transition Model for Pedestrian Dynamics," Springer Books, in: Ulrich Weidmann & Uwe Kirsch & Michael Schreckenberg (ed.), Pedestrian and Evacuation Dynamics 2012, edition 127, pages 971-985, Springer.
  • Handle: RePEc:spr:sprchp:978-3-319-02447-9_81
    DOI: 10.1007/978-3-319-02447-9_81
    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:sprchp:978-3-319-02447-9_81. 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.