A Correlated Random Parameter Approach to Investigate Effects of Weather Conditions on Crash Risk for a Mountainous Freeway

Freeway crashes are highly influenced by weather conditions, especially for a mountainous freeway affected by adverse weather conditions. In order to reduce crash occurrence, a variety of weather monitoring systems and Intelligent Transportation Systems (ITS) have been introduced to address the weather impact. The effects of weather conditions on crash occurrence have not been fully investigated and understood. With detailed weather information from weather monitoring stations, this study seeks to investigate the complex effects of weather factors, such as visibility and precipitation, on crash occurrence based on safety performance functions. Unlike conventional traffic safety studies which deal with crash frequency, crash rates per 100-million vehicle miles travelled were adopted as the dependent variable in this study. Three years of weather related crash data from a 15-mile mountainous freeway on I-70 in Colorado were utilized. First, a fixed parameter Tobit model was estimated to unveil the effects of explanatory variables on crash rates. Then, in order to characterize the heterogeneous effects of weather conditions across the homogeneous segments, a traditional random parameter Tobit model was developed. Furthermore, for the purpose of monitoring the intricate interactions between weather conditions and geometric characteristics, a multivariate structure for the distribution of random parameters was introduced; which result in a correlated random parameter Tobit model. Likelihood ratio test results demonstrated that the correlated random parameter Tobit model was superior to the uncorrelated random parameter and fixed parameter Tobit models. Moreover, visibility and precipitation variables were found to have substantial correlation effects with geometric characteristics like steep downgrade slopes and curve segments. Results from the models would shed lights on future applications of weather warning systems to improve traffic safety.

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

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Yu, Rongjie
  • Xiong, Yingge
  • Abdel-Aty, Mohamed A
• 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: References; Tables;
• Pagination: 20p
• Monograph Title: TRB 93rd Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Crash rates; Crash risk forecasting; Data analysis; Freeways; Highway curves; Highway safety; Intelligent transportation systems; Mathematical models; Mountain roads; Precipitation (Meteorology); Road downgrades; Visibility; Warning systems; Weather conditions
• Geographic Terms: Colorado
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; I81: Accident Statistics; I82: Accidents and Transport Infrastructure;

Filing Info

• Accession Number: 01520357
• Record Type: Publication
• Report/Paper Numbers: 14-0540
• Files: TRIS, TRB, ATRI
• Created Date: Mar 27 2014 3:38PM