IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-662-10583-2_14.html
   My bibliography  Save this book chapter

Breakdown and Recovery in Traffic Flow Models

In: Traffic and Granular Flow’01

Author

Listed:
  • K. Nagel

    (ETH Zürich, Department of Computer Science)

  • C. Kayatz

    (ETH Zürich, Department of Computer Science)

  • P. Wagner

    (German Aerospace Centre, Institute for Transportation Research)

Abstract

Most car-following models show a transition from laminar to “congested” flow and vice versa. Deterministic models often have a density range where a disturbance needs a sufficiently large critical amplitude to move the flow from the laminar into the congested phase. In stochastic models, it may be assumed that the size of this amplitude gets translated into a waiting time, i.e. until fluctuations sufficiently add up to trigger the transition. A recently introduced model of traffic flow however does not show this behavior: in the density regime where the jam solution co-exists with the high-flow state, the intrinsic stochasticity of the model is not sufficient to cause a transition into the jammed regime, at least not within relevant time scales. In addition, models can be differentiated by the stability of the outflow interface. We demonstrate that this additional criterion is not related to the stability of the flow. The combination of these criteria makes it possible to characterize similarities and differences between many existing models for traffic in a new way.

Suggested Citation

  • K. Nagel & C. Kayatz & P. Wagner, 2003. "Breakdown and Recovery in Traffic Flow Models," Springer Books, in: Minoru Fukui & Yuki Sugiyama & Michael Schreckenberg & Dietrich E. Wolf (ed.), Traffic and Granular Flow’01, pages 141-153, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-10583-2_14
    DOI: 10.1007/978-3-662-10583-2_14
    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:978-3-662-10583-2_14. 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.