Pedestrian-Vehicle Interaction in a CAV Environment: Explanatory Metrics

Details

• Alternative Title:
  Translation of Driver-Pedestrian Behavioral Models at Semi-Controlled Crosswalks Into a Quantitative Framework for Practical Self-Driving Vehicle Applications
• Creators:
  Zhang, Yunchang ; Fricker, Jon D.
• Corporate Creators:
  Center for Connected and Automated Transportation (CCAT) ; Purdue University ; University of Michigan. Transportation Research Institute
• Corporate Contributors:
  United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  • Autonomous vehicle guidance
  • Congestion management systems
  • Connected vehicles
  • Human factors engineering
  • Policy
  • Traffic control
  • Vulnerable road users
  • Crosswalks
• Publication/ Report Number:
  CCAT Report #61
• DOI:
  http://dx.doi.org/10.5703/1288284317575
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report. 01/01/2020 12/31/2021
• Corporate Publisher:
  University of Michigan. Center for Connected and Automated Transportation ; Center for Connected and Automated Transportation. Purdue University
• Abstract:
  The research described in this report was motivated by frequent questions from users of several crosswalks near a university campus. At each crosswalk was a sign indicating that motorists should yield to pedestrians in the crosswalk. The notion that this message was not being interpreted uniformly was a concern at locations where heterogeneous road users (pedestrians, cyclists, and motorists) were interacting. Instead of trying to impose a single interpretation on users of each crosswalk, it was decided to observe and analyze interactions between users of the crosswalk.
• Format:
  PDF
• Funding:
  69A3551747105
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/72953/dot_72953_DS1.pdf
• File Type:
  [PDF - 2.28 MB]
• Collection(s):
  Autonomous Vehicles ; University Transportation Centers
• Main Document Checksum:
  urn:sha-512:c8319608612e14feec6df6d16aa480ffdc10cf1eecc5b9dbe407296d9332278d320176afd74fe90b18f239053ace2fe9bae854f175c088a20255fec7fdef8263