Enhancing automated vehicle safety through testing with realistic driver models
Improving safety during interactions between human drivers and automated vehicles requires an environment where autonomous vehicle software can interact with realistic human driving behavior. Generating this behavior has been challenging due to a lack of driver models that accurately reflect both vehicle kinematics and driver cognition. In this project, the research team proposes to develop an active inference model of car-following behavior that will resolve these limitations. The model will be trained using the UC Berkeley INTERACTION dataset. After training, the team will work with Waymo to validate the model on an internal dataset and, if necessary, implement a set of augmentations that will allow the model to be used to improve the safety of autonomous vehicle interactions with human drivers
Language
- English
Project
- Status: Active
- Funding: $150000
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Contract Numbers:
69A3551747115
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
Safety through Disruption University Transportation Center (Safe-D)
Virginia Tech Transportation Institute
Blacksburg, VA United States 24060 -
Project Managers:
Glenn, Eric
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Performing Organizations:
Texas A&M Transportation Institute, College Station
Texas A&M University System
3135 TAMU
College Station, TX United States 77843-3135 -
Principal Investigators:
McDonald, Tony
- Start Date: 20220115
- Expected Completion Date: 20230630
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Behavior; Car following; Drivers; Highway safety
- Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01835030
- Record Type: Research project
- Source Agency: Safety through Disruption University Transportation Center (Safe-D)
- Contract Numbers: 69A3551747115
- Files: UTC, RIP
- Created Date: Jan 31 2022 10:38AM