Effect of Road Characteristics and Driving Cycles on Accident Risk on Full-Access-Control Highways

Crashes on freeways have caused severe life and property losses in the United States. In order to better predict crash risk on full - access - control roads, the correlation between crash rate and traffic factors (such as speed and speed variance) along with roadway characteristic s (such as number of through lanes, functional system) is studied in this paper with Naturalistic Driving Study data. The traffic characteristics considered in this paper were extracted from driving cycles that were generated from the SHRP 2 database. A total of 1,089 road segments with driving cycles information and crash rate information were reserved for regression analysis. A negative binomial model for freeway crash rate prediction was developed to evaluate the effect of different factors on the incidence of crashes on full-access-control highways. The diagnostics plots approved that negative binomial is a valid model for the data. The coefficient value and its significance level were estimated for each of the selected variables. For roadway characteristics, the results of the analysis indicate that for an urban area, the number of through lanes in one direction and speed limits have a significant influence on the crash risk, while functional system, curve level, and grade level have less of an effect on crash risk. For traffic factors, high average speed and high fluctuation in vehicle speed will significantly increase crash rate. The results of this research can be used to help engineers predict crash risk at different highway locations and take measures to improve traffic safety on full - access - control highways.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ANB20 Standing Committee on Safety Data, Analysis and Evaluation.
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Wu, Jianqing
    • Xu, Hao
    • Sun, Yuan
    • Geng, Xinli
  • Conference:
  • Date: 2017

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 13p
  • Monograph Title: TRB 96th Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01623698
  • Record Type: Publication
  • Report/Paper Numbers: 17-00940
  • Files: TRIS, TRB, ATRI
  • Created Date: Jan 25 2017 3:08PM