Development of AI-Based and Control-Based Systems for Safe and Efficient Operations of Connected and Autonomous Vehicles

Details

• Creators:
  Dong, Jiqian ; Du, Runjia ; Ha, Paul (Young Joun) ; Chen, Sikai ; Labi, Samuel
• Corporate Creators:
  Purdue University ; Center for Connected and Automated Transportation (CCAT)
• Corporate Contributors:
  United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology ; United States. Department of Transportation. University Transportation Centers (UTC) Program
• Subject/TRT Terms:
  • Autonomous vehicles
  • Infrastructure
  • Artificial intelligence
  • Control
  • Crashes
  • Laser radar
  • Vehicle electronics
  • Lane changing
  • Crash avoidance systems
  • information fusion
• Publication/ Report Number:
  41
• DOI:
  http://dx.doi.org/10.5703/1288284317571
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final report, Jan 2019 - Dec 2020
• Corporate Publisher:
  University of Michigan. Center for Connected and Automated Transportation
• Abstract:
  Autonomous vehicles (AVs) are an emerging theme for future transportation. However, research on pedestrian-AV interaction, which promotes pedestrian safety during autonomous driving, is not a well-explored domain. One challenge preventing the development of pedestrian-AV interaction research is that there is no publicly available and standardized benchmark to allow researchers to investigate how different interfaces could help pedestrians communicate with AVs. To resolve this challenge, we introduce the Virtual Reality Pedestrian-Autonomous Vehicle Interaction Benchmark (VRPAVIB). VR-PAVIB is a standardized platform that can be used to reproduce interaction scenarios and compare results. Our benchmark provides state-of-the-art functionalities that can easily be implemented in any interaction scenario authored by a user. The VR-PAVIB can easily be used in a controlled lab space using low-cost virtual reality equipment. We have released our project code and include the automotive user interface community to extend VR-PAVIB.
• Format:
  PDF
• Funding:
  69A3551747105
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/72965/dot_72965_DS1.pdf
• File Type:
  [PDF - 2.90 MB]
• Collection(s):
  Artificial Intelligence Deployment Center of Excellence (AI COE) ; Autonomous Vehicles ; University Transportation Centers
• Main Document Checksum:
  urn:sha-512:c3ab7cdd294502896edf55fdf681f24f62e27ba133b91090278a5f4592920ae737ba1532caece0845f81a015055c754c672921fe2ca376500f39a5b1972dbe5d