IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v594y2022ics0378437122001078.html
   My bibliography  Save this article

Statistical aspects of gap-acceptance theory for unsignalized intersection capacity

Author

Listed:
  • Krbálek, Milan
  • Hobza, Tomáš
  • Patočka, Miroslav
  • Krbálková, Michaela
  • Apeltauer, Jiří
  • Groverová, Nikola

Abstract

We partially correct and significantly deepen the Siegloch’s method (1973), which is currently used to determine the capacity of unsignalized intersections. Taking into account current knowledge about microstructure of vehicular traffic flows we suggest Generalized Inverse Gaussian distribution as a theoretically and empirically substantiated alternative to the exponential distribution of priority-stream clearances, considered in Siegloch’s original methodology. Furthermore, we formulate a statistical model for gap-acceptance theory and present a series of validated theoretical calculations leading to general formulas for proportion and statistical distribution of priority-stream clearances that exactly k minor-stream vehicles have utilized for their inclusion maneuver (accepted-clearance distribution of order k). Using up-to-date empirical data-sets we test hypotheses of priority-stream clearance-distribution and analyze sample acceptance-ratios and empirical distribution of accepted clearances. By means of an original concept we finally estimate an implicit acceptance-rule, with the help of which a minor-street driver is deciding on acceptance/rejection of an offered priority-clearance.

Suggested Citation

  • Krbálek, Milan & Hobza, Tomáš & Patočka, Miroslav & Krbálková, Michaela & Apeltauer, Jiří & Groverová, Nikola, 2022. "Statistical aspects of gap-acceptance theory for unsignalized intersection capacity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
  • Handle: RePEc:eee:phsmap:v:594:y:2022:i:c:s0378437122001078
    DOI: 10.1016/j.physa.2022.127043
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437122001078
    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.2022.127043?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. Chen, Xiaolong & Hu, Manjiang & Xu, Biao & Bian, Yougang & Qin, Hongmao, 2022. "Improved reservation-based method with controllable gap strategy for vehicle coordination at non-signalized intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    2. Qin, Yanyan & Luo, Qinzhong & Xiao, Tengfei & He, Zhengbing, 2024. "Modeling the mixed traffic capacity of minor roads at a priority intersection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).

    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:594:y:2022:i:c:s0378437122001078. 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.