Smart Interaction – Pedestrians and Vehicles in a CAV Environment

At “semi-controlled” crosswalks with yield signs and markings, negotiations as to the right-of-way occur frequently between pedestrians and motorists, to determine who should proceed first. This kind of “negotiation” often leads to traffic delay and potential conflicts. To minimize misunderstandings between pedestrian and motorist that can have serious safety consequences, it is essential that we understand the decision-making process as they interact in real street-crossing situations. This project employs a game-theoretic approach to investigate the joint behaviors of pedestrians and motorists from the perspective of safety. Assuming bounded rationality for each player, the quantal response equilibrium is a special kind of game with incomplete information. Explanatory variables such as conflicting risks and time savings can be incorporated into the payoff functions of the “players” via expected utility functions. Finally, model parameters can be estimated using an expectation maximization algorithm. The game-theoretic framework is applied to model pedestrian-motorist interactions at a semi-controlled crosswalk on a university campus. The estimation results indicate that the likelihood of pedestrian-vehicle conflict can be quantified. The results can lead to control measures that facilitate the negotiation between pedestrian and motorist and reduce the conflict risk at semi-controlled crosswalks and can help the design of an intelligent risk assessment system at crosswalks.

• Record URL:
  • https://doi.org/10.5703/1288284317574
• Record URL:
  • https://rosap.ntl.bts.gov/view/dot/72934
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Center for Connected and Automated Transportation

  University of Michigan Transportation Research Institute
  Ann Arbor, MI  United States  48109

  Purdue University

  West Lafayette, IN  United States  47907-2051

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Zhang, Yunchang
  • 0000-0001-7803-003X
  • Fricker, Jon D
• Publication Date: 2022-6

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Appendices; Figures; Photos; References; Tables;
• Pagination: 39p

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Behavior; Connected vehicles; Crosswalks; Decision making; Game theory; Pedestrians; Risk assessment
• Subject Areas: Highways; Pedestrians and Bicyclists; Planning and Forecasting; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01903851
• Record Type: Publication
• Report/Paper Numbers: 36
• Contract Numbers: 69A3551747105
• Files: UTC, NTL, TRIS, USDOT
• Created Date: Jan 2 2024 9:18AM