IDEAS home Printed from https://ideas.repec.org/p/cdl/itsdav/qt106268rb.html
   My bibliography  Save this paper

How Intelligent Vehicle Technologies Can Improve Vulnerable Road User Safety at Signalized Intersections

Author

Listed:
  • Qian, Xiaodong
  • Xiao, Runhua
  • Jaller, Miguel
  • Chen, Shenyang

Abstract

Motor vehicle crashes are the leading cause of accidental deaths in the US. In 2020, 38,824 people lost their lives in car-related crashes. Bicyclists and pedestrians are particularly susceptible—7,448 of these “vulnerable road users” were killed nationwide in 2020, and 29% of all reported crash-related fatalities in California were vulnerable road users. A variety of intelligent vehicle technologies hold promise for improving bicycle and pedestrian safety. Sensors in vehicles and/or used by vulnerable road users themselves could alert travelers of potential conflicts, giving them more time to react. However, these technologies all have unique technical, operational, and financial characteristics, and they might perform differently in different environmental conditions and at different levels of deployment. Little research has been done on how these technologies might affect safety. Researchers at the University of California, Davis combined aggregate historical crash data analysis and micro transportation simulation to examine the safety impacts of four different intelligent vehicle technologies: blind spot detection, a vulnerable-road-user beacon system carried by bicyclists or pedestrians, bicycle/pedestrian-to-vehicle communication, and intersection safety. View the NCST Project Webpage

Suggested Citation

  • Qian, Xiaodong & Xiao, Runhua & Jaller, Miguel & Chen, Shenyang, 2022. "How Intelligent Vehicle Technologies Can Improve Vulnerable Road User Safety at Signalized Intersections," Institute of Transportation Studies, Working Paper Series qt106268rb, Institute of Transportation Studies, UC Davis.
  • Handle: RePEc:cdl:itsdav:qt106268rb
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/106268rb.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Engineering; Social and Behavioral Sciences; Intelligent vehicles; Sight distance; Signalized intersections; Traffic safety; Traffic simulation; Traffic volume; Vulnerable road user;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cdl:itsdav:qt106268rb. 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucdus.html .

    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.