Development of machine-learning models for autonomous vehicle decisions on weaving sections of freeway ramps
To date no systems can recommend when and how lane changes should be made in weaving sections with limited length to ensure that traffic stays safely and smoothly separated. This study aims to (1) investigate drivers’ decision and speed control before changing lanes into/out of the weaving section, (2) develop the lane change decision and maneuver algorithms for automated vehicles (AVs), (3) apply the algorithms to AVs, and (4) validate the algorithms on Mcity Test Facility. Two types of model/algorithm will be created to (1) identify the surrounding vehicle characteristics, and (2) classify drivers’ decision to change lanes and model the lane change maneuvers in the weaving section. The validation taking place on Mcity will provide evidence to test and improve the algorithms, as well as a demonstration to showcase how the AV can interact with weaving vehicles.
Language
- English
Project
- Status: Active
- Funding: $145,429
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Contract Numbers:
69A3551747105
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Sponsor Organizations:
Department of Transportation
Intelligent Transportation Systems Joint Program Office
1200 New Jersey Avenue, SE
Washington, DC United States 20590 -
Managing Organizations:
Center for Connected and Automated Transportation
University of Michigan, Ann Arbor
Ann Arbor, MI United States 48109 -
Project Managers:
Tucker-Thomas, Dawn
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Performing Organizations:
University of Michigan Transportation Research Institute
2901 Baxter Road
Ann Arbor, Michigan United States 48109 -
Principal Investigators:
Lin, Brian
- Start Date: 20190701
- Expected Completion Date: 20220930
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
- Subprogram: Research
Subject/Index Terms
- TRT Terms: Algorithms; Automated guided vehicle systems; Autonomous vehicles; Classification; Connected vehicles; Lane changing; Maneuvering; Test facilities; Vehicle characteristics; Weaving sections; Weaving traffic
- Identifier Terms: Mcity
- Subject Areas: Education and Training; Policy; Research; Safety and Human Factors; Transportation (General); Vehicles and Equipment;
Filing Info
- Accession Number: 01742585
- Record Type: Research project
- Source Agency: Center for Connected and Automated Transportation
- Contract Numbers: 69A3551747105
- Files: UTC, RIP
- Created Date: Jun 18 2020 8:42AM