Enabling Technology for Connected and Automated Vehicles

Analysis, Modeling, and Simulation (AMS) tools will be advanced through the collection and dissemination of new and existing datasets of on-road observations of and experimental data on the behavior of autonomous vehicles (AVs) in traffic for future integration into microsimulation programs and analytical processes. This objective is to transfer new AMS capabilities to industry to assist Infrastructure Owners and Operators (IOOs) in assessing the performance of connected and automated vehicles (CAVs) as they are tested and deployed on the Nation's roadways. Additionally, this research includes assessment of how Artificial Intelligence and Machine Learning (AI/ML) can be incorporated into Transportation Systems Management and Operations (TSMO) concepts. This project also supports the management and operations of the Saxton Transportation Operations Lab (STOL). Components of this research started in FY19 through FY21 and will continue through FY22 to FY26, respectively.

• Supplemental Notes:
  • USDOT Research Hub DisplayID 157832

Language

• English

Project

• Status: Active
• Funding: $4663462
• Sponsor Organizations:

  Federal Highway Administration

  ,    
• Managing Organizations:

  Federal Highway Administration

  Office of Operations Research and Development
  Washington, DC    20590
• Project Managers:

  Vangorder, Randall

• Start Date: 20190815
• Expected Completion Date: 20221231
• Actual Completion Date: 0
• USDOT Program: Automation and Connectivity

Subject/Index Terms

• TRT Terms: Artificial intelligence; Autonomous vehicles; Connected vehicles; Data analysis; Machine learning; Simulation; Transportation system management
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01864218
• Record Type: Research project
• Source Agency: Department of Transportation
• Files: RIP, USDOT
• Created Date: Nov 17 2022 11:56AM