Impact of Access Management on Driver Behaviors

Details

• Creators:
  Cuddy, Matthew ; Abodo, Franklin ; Black, Laura ; Bryan, Karna ; Dogan, Amelia ; Fisher, Donald ; Gabree, Scott ; Jantz, Sophie ; Patel, Julie
• Corporate Creators:
  John A. Volpe National Transportation Systems Center (U.S.)
• Corporate Contributors:
  Governors Highway Safety Association ; United States. Department of Transportation. National Highway Traffic Safety Administration. Office of Behavioral Safety Research
• Subject/TRT Terms:
  • Roundabouts
  • Traffic circles
  • Driver errors
  • Automatic data collection systems
  • Driving behavior
  • driver uncertainty
  • driver hesitation
  • SHRP2-NDS
• Publication/ Report Number:
  DOT HS 813 440
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Corporate Publisher:
  United States. Department of Transportation. National Highway Traffic Safety Administration
• Abstract:
  This project started with a broad question: What can new, rich naturalistic driver data such as in the Second Strategic Highway Research Program's Naturalistic Driving Study (SHRP2-NDS), tell us about how drivers react to roadway designs and access management techniques? To address this question, the project team reviewed and analyzed 6,209 trips that drivers in the NDS took through 40 circular intersections across five States. Coders flagged several types of driver behavior and captured a broad range of contextual variables. The analysis team used traditional statistics and machine learning methods to understand (1) when driver hesitation or uncertainty is most likely, and (2) general patterns and trends in driver hesitation or uncertainty. The team found that driver age is the most important predictor of hesitation or uncertainty with drivers' engagement in secondary tasks being a strong second. The findings presented here suggest further development and dissemination of educational or informational materials could mitigate drivers' hesitation or uncertainty in circular intersections and thereby improve traffic safety.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/68310/dot_68310_DS1.pdf
• File Type:
  [PDF - 857.06 KB]
• Collection(s):
  Artificial Intelligence Deployment Center of Excellence (AI COE) ; Volpe Center ; NHTSA - Behavioral Safety Research
• Main Document Checksum:
  urn:sha-512:649f0f2a75ae5fd32f07d60cbfb3965703c49f52e0d7723b52ddd3e6a6890eb4b6d155ea7edf0887379c81c1faea72564701093d80204139f88ae39add597238