Identify High Crash Risk Locations for Rural Roadways: A Systemic Approach to Reduce Severe and Fatal Traffic Crashes in Louisiana and Mississippi

Details

• Creators:
  Sun, Xiaoduan ; Rahman, M.
• Corporate Creators:
  National Center for Intermodal Transportation for Economic Competitiveness ; Mississippi State University
• Corporate Contributors:
  University of Louisiana at Lafayette. Dept. of Civil Engineering ; United States. Department of Transportation. Research and Innovative Technology Administration
• Subject/TRT Terms:
  • Annual average daily traffic
  • Crash rates
  • Drunk driving
  • Fatalities
  • High risk locations
  • Highway curves
  • Rural highways
  • Single vehicle crashes
  • Two lane highways Curve radius
  • Surface condition
  More +
• Publication/ Report Number:
  NCITEC Project 2016-10
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States;Mississippi;Louisiana
• Corporate Publisher:
  Mississippi State University. National Center for Intermodal Transportation for Economic Competitiveness
• Abstract:
  Louisiana is among the top crash and fatality overrepresented states with a much higher the national average crash and fatality rates. Traditional approach on high risk crash location identification does not work effectively on locations with low traffic volumes, such as rural and local roadways where bears low design standards. Systemic approach is a proactive way for critical crash location identification based on the roadway geometry and characteristics of locations. Rural two-lane roadways have much higher fatal crash rate than any other roadways. On Louisiana state-maintained rural two-lane roadways, most predominant crash types, “non-collision” single vehicle crashes (79%) on curves are more prevalent than on tangent sections and intersections. By using GIS and logistic regression model, this study investigate relationship between roadway geometric and driver characteristics and crash risk on rural two-lane curves. The analysis results reveal that the key crash contributing factors are alcohol involvement, surface condition, AADT, and radius of the curve.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/39854/dot_39854_DS1.pdf
• File Type:
  [PDF - 1021.12 KB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:b901c63bc6936ffcd0808bfd14e97d0138e480beda108546bafed69c2729b6cdb2918eeea720a2120cc20a4eb8197db0faad94623fc0ac95dba3f7a463191f5f