A Study on Traffic Incident Detection Using Sensing Information from Roadside Infrastructure

In order to help to reduce traffic accidents, it is important to identify, analyze, and find the hidden causes of traffic accidents. In this study, attention is paid to the traffic incidents at intersections. In Japan, about 55 percent of the traffic accidents have happened at intersections. The sensors on the roadside infrastructure have an ability to detect the position, shape, and the speed of each vehicle accurately from the bird’s eye view. The overcrowded intersection, however, adds unpredictable errors onto sensing information. This paper proposes the traffic incident detection method based on the speed estimation with the unpredictable error tolerance against disturbance. Moreover, the effectiveness of the proposed method is verified through the simulation study. The potential variations of the observed speed data are generated by adding the observational errors, which are simulated by randomly sampling the error distributions using the normal distribution, to the actual speed data of the real accidents.

• Availability:
  • Find a library where document is available. Order URL: http://itswc.confex.com/itswc/WC2011/webprogram/start.html
• Supplemental Notes:
  • Abstract reprinted with permission from Intelligent Transportation Society of America.
• Corporate Authors:

  ITS America

  1100 17th Street, NW, 12th Floor
  Washington, DC  United States  20036
• Authors:
  • Emura, Koichi
• Conference:
  • 18th ITS World Congress
  • Location: Orlando Florida, United States
  • Date: 2011-10-16 to 2011-10-20
• Publication Date: 2011

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 8p
• Monograph Title: 18th ITS World Congress, Orlando, 2011. Proceedings

Subject/Index Terms

• TRT Terms: Automatic incident detection; Data quality; Error analysis; High risk locations; Intersections; Sensors; Simulation; Speed data
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; I80: Accident Studies;

Filing Info

• Accession Number: 01449474
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 18 2012 5:10PM