Evaluation of Peak Over Threshold Approach for Road Safety Estimation

Development of non-crash-based safety estimation approaches has drawn considerable research interest, and the application of extreme value theory is one of them. This study proposes the use of extreme value theory based peak over threshold (POT) approach for road safety estimation and compares the POT with the crash-based negative binomial regression approach. The traffic data is from videos recorded at 29 directional segments with time duration of approximately 3 h each. The results show that the best fitted model comes from regression model with R2 of 0.65, in which the covariate is return levels estimated from POT approach. Meanwhile, the POT estimated crashes also have relatively high R2 value but with large variances. Both of these imply that POT estimations from short observation time carry useful safety information. Moreover, the POT estimated return levels can be employed as a covariate for building better regression models.

• Record URL:
  • https://doi.org/10.1080/19439962.2014.904029
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/19439962
• Supplemental Notes:
  • Abstract reprinted with permission of Taylor & Francis.
• Authors:
  • Zheng, Lai
  • Ismail, Karim
  • Meng, Xianghai
• Publication Date: 2015-1

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 76-90
• Serial:
  • Journal of Transportation Safety & Security
  • Volume: 7
  • Issue Number: 1
  • Publisher: Taylor & Francis
  • ISSN: 1943-9962
  • EISSN: 1943-9970
  • Serial URL: http://www.tandfonline.com/loi/utss20#.U2qTJPldWCm

Subject/Index Terms

• TRT Terms: Estimating; Highway safety; Mathematical models; Real time information; Regression analysis; Risk assessment; Traffic density; Traffic flow
• Subject Areas: Highways; Operations and Traffic Management; I72: Traffic and Transport Planning; I73: Traffic Control;

Filing Info

• Accession Number: 01545547
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 26 2014 3:07PM