Traffic Accident Risk Estimation Based on the Lognormal Hurdle Model with a Flexible Scale Parameter

Comprehensive measures of accident risks are critical for the risk assessment of specific transportation facilities during a safety planning process. Different with the frequently used accident rate, this study introduces a criterion that integrates both information of accident occurrence and more importantly the overall harmfulness resulted from accidents. It also forms a general definition of accident risks, which provides a single value to comprehensively capture the losses brought by accidents. In order to understand the distributional characteristics of the introduced risk measures as well as construct its relationship with factors, a hurdle model with lognormal specifications is suggested for regression purposes. An observed dataset is adopted in this study for applying the proposed model which in fact provides preponderance of regression on both location and scale parameters for the right-hurdle part, whereas the traditional lognormal analysis assumes constant scale parameters across all observations. Based on the regression results, the impacts of explanatory variables on the accident risks are also examined.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ANB20 Safety Data, Analysis and Evaluation. Alternate title: Traffic Accident Risk Estimation Based on Lognormal Hurdle Model with Flexible Scale Parameter.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Ma, Lu
  • Yan, Xuedong
  • Zhang, Cuiping
  • Weng, Jinxian
• Conference:
  • Transportation Research Board 93rd Annual Meeting
  • Location: Washington DC
  • Date: 2014-1-12 to 2014-1-16
• Date: 2014

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Maps; References; Tables;
• Pagination: 17p
• Monograph Title: TRB 93rd Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Crash risk forecasting; Crash severity; High risk locations; Highway factors in crashes; Loss and damage; Risk analysis
• Geographic Terms: Pikes Peak Region (Colorado)
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; I82: Accidents and Transport Infrastructure;

Filing Info

• Accession Number: 01518590
• Record Type: Publication
• Report/Paper Numbers: 14-3703
• Files: TRIS, TRB, ATRI
• Created Date: Mar 20 2014 1:39PM