Multiple-vehicle Trajectory Planning Framework Considering Vulnerable Road Users

Details

• Creators:
  Shen, Di ; Shi, Xiaowei ; Qin, Xiao
• Corporate Creators:
  Center for Pedestrian and Bicyclist Safety (CPBS) Tier-1 University Transportation Center (UTC) ; University of Wisconsin--Milwaukee
• 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 Vehicles Connected Vehicles Traffic Safety Trajectory Control Vehicle Design Vulnerable Road Users
• Publication/ Report Number:
  23UWM07
• DOI:
  https://doi.org/10.21949/2cdw-te21
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report – June 2023 to May 2024
• Corporate Publisher:
  Center for Pedestrian and Bicyclist Safety (CPBS) Tier-1 University Transportation Center (UTC)
• Abstract:
  Connected and Automated Vehicles (CAVs) promise enhanced traffic safety through precise, sensor-based control, but their effectiveness depends on accurately predicting and responding to the interactions between CAVs and Vulnerable Road Users (VRUs). This project addresses three main technical questions: modeling the multi-agent decision-making process for CAVs, incorporate and anticipate VRUs' responses to CAVs in modeling, and solving these challenges in real-time. Utilizing game theory and a discrete-time Markov sequential game framework, the interactions between CAVs and VRUs are modeled to maximize utility while accounting for the dynamic nature of VRU behavior. To achieve real-time implementation, efficient heuristics algorithms are developed, combining customized dynamic programming and adaptive algorithms. Numerical simulations validate the proposed model, highlighting its effectiveness in managing interactions in a two-lane traffic scenario with a crosswalk. The findings underscore the potential of this approach to significantly improve the operational safety of CAVs in mixed traffic environments.
• Format:
  PDF
• Funding:
  69A3552348336
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:d6157cd6cb3352535f17774a2b57c88523d4a9198cd45e8ece7142cb61fee26b0a631959cabe730e6cb2e1efa60bfc6e99ecb7911467a25cbb3e381e78064121
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/86200/dot_86200_DS1.pdf
• File Type:
  [PDF - 885.51 KB ]