IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-319-10629-8_15.html
   My bibliography  Save this book chapter

Dynamic Data–Driven Simulation of Pedestrian Movement with Automatic Validation

In: Traffic and Granular Flow '13

Author

Listed:
  • Jakub Porzycki

    (AGH University of Science and Technology, Department of Applied Computer Science)

  • Robert Lubaś

    (AGH University of Science and Technology, Department of Applied Computer Science)

  • Marcin Mycek

    (AGH University of Science and Technology, Department of Applied Computer Science)

  • Jarosław Wąs

    (AGH University of Science and Technology, Department of Applied Computer Science)

Abstract

The article presents a dynamic data-driven simulation of pedestrian movement based on the generalized Social Distances Model, where a simulation system is continuously synchronized with current flow data, gained from Microsoft Kinect depth map. Both simulation and data analysis are real-time processes. Agent appears in simulation, as soon as consecutive pedestrians leave sensors tracking zone. Due to system architecture containing feedback loop, automatic validation and parameters calibration is possible. A new method of depth map based pedestrian tracking is proposed as well as a new algorithm of pedestrian parameters extraction for short trajectories. The paper describes in detail the proposed algorithms, system architecture and an illustrative experiment.

Suggested Citation

  • Jakub Porzycki & Robert Lubaś & Marcin Mycek & Jarosław Wąs, 2015. "Dynamic Data–Driven Simulation of Pedestrian Movement with Automatic Validation," Springer Books, in: Mohcine Chraibi & Maik Boltes & Andreas Schadschneider & Armin Seyfried (ed.), Traffic and Granular Flow '13, edition 127, pages 129-136, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-10629-8_15
    DOI: 10.1007/978-3-319-10629-8_15
    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:978-3-319-10629-8_15. 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.