Proactive assessment of accident risk to improve safety on a system of freeways : [research brief].

Details

• Creators:
  Pande, Anurag ; Nuworsoo, Cornelius ; Shew, Cameron
• Corporate Creators:
  Mineta Transportation Institute
• Corporate Contributors:
  California. Dept. of Transportation. Office of Research ; United States. Department of Transportation. Research and Innovative Technology Administration
• Subject/TRT Terms:
  • Real time data processing
  • Real time information
  • Information systems
  • Data mining
  • Data processing operations
  • Decision trees
  • Loop detectors Real-time crash risk
  • Data mining
  • Classification tree
  • Proactive traffic management
  More +
• Publication/ Report Number:
  MTI Project 1006
• Resource Type:
  Tech Report
• Geographical Coverage:
  California
• Edition:
  Research brief.
• Corporate Publisher:
  Mineta Transportation Institute
• Abstract:
  As traffic safety on freeways continues to be a growing concern, much progress has been made in shifting from reactive (incident detection) to proactive (real-time crash risk assessment) traffic strategies. Reliable models that can take in real-time loop detector information and discern normal flow from crash-prone conditions are a key to implementing crash preventive measures.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/24329/dot_24329_DS1.pdf
• File Type:
  [PDF - 313.54 KB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:b79e4c68ae25b665d819456ba8675dcbf4209825d1c16cdcb1f1ade6cfe2b3ed6d63982786e82ec6c70b1b3ff60b1f680cb9fb10b12fd0c0a723977c9e724426