Risk Aware Warning and Control for Interactive Traffic Safety

Details

• Creators:
  Dolan, John M ; Lyu, Yiwei ; Schulte, Paul
• Corporate Creators:
  Carnegie Mellon University. Traffic21 University Transportation Center (UTC) ; Carnegie-Mellon University. Robotics 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 vehicles
  • Driver support systems
  • Lane changing
  • Merging traffic
  • Risk assessment
  • Traffic safety
  • Highways
  • Human factors
  • Safety
  • Risk management Highways
  More +
• Publication/ Report Number:
  428
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report
• Corporate Publisher:
  Carnegie Mellon University. Traffic21 Institute. Safety21 University Transportation Center (UTC)
• Abstract:
  In this project, we proposed a CBF-inspired risk assessment toolbox, measuring the aggregated risk faced by individual agents due to multi-agent interactions, to help empower the ego robot with a comprehensive understanding of the dynamic environment it is in. We also demonstrate two complementary methodologies of embedding the resulting risk assessment into robot controller design, especially for multi-robot scenarios. We show how to utilize such risk information to perform partition in robots’ joint state and action space respectively to construct robot controllers, resulting in the proposed Risk-aware WBVC and Risk-aware decentralized CBF. We further demonstrated the general applicability of our risk assessment in deployment to a physical F1-Tenth testing platform with existing MPPI-based vehicle controllers. A safe and efficient overtaking scenario is demonstrated. In the future, we are interested in extending these methods for safe navigation for self-driving cars with learning-enabled components.
• Format:
  PDF
• Funding:
  69A3552344811
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/77710/dot_77710_DS1.pdf
• File Type:
  [PDF - 26.42 MB]
• Collection(s):
  Autonomous Vehicles ; University Transportation Centers
• Main Document Checksum:
  urn:sha-512:abcaaaacc3476e55593fcd45994100ff847c26056c289370017da94bef68fd9099bbe10a123db6af5a35e0c8d5e957ab1e06869e086a499ad3fb7e747fb29f10