A Naturalistic Bicycling Study in the Ann Arbor Area
In the past few years much progress have been made in the self-driving technologies and related issues (e.g., legislation and regulation) by a variety of entities from automotive and tech industries, academic institutions, and government and organizations. However, there are still great challenges to be solved. One of the critical challenges is that the self-driving cars need to share the existing infrastructure with other non-motorized road users such as bicyclists and pedestrians. Given the complexity of the real-world road environment and the presumably high variability of the behaviors of the non-motorized road users, how the self-driving cars should be designed, tested, and tuned to share the road with bicyclists and pedestrians in a safe and efficient manner is a complicated and yet crucial question. One way to potentially help answer this question is to collect naturalistic data of people riding bicycles in their everyday trips on real-world roadways, and use the collected quantitative data to create guidelines, supports, and test scenarios to develop the artificial intelligence algorithms for self-driving cars in their ability to effectively interact with bicyclists in real-world environment. The final report for this project will not be publicly available.
Language
- English
Project
- Status: Completed
- Funding: $369,104 Toyota (100% Cost Share)
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Contract Numbers:
69A3551747105
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Sponsor Organizations:
University Transportation Center Program
1200 New Jersey Avenue, SE
Washington, DC United States 20590University of Michigan Transportation Research Institute
2901 Baxter Road
Ann Arbor, Michigan United States 48109 -
Managing Organizations:
University of Michigan Transportation Research Institute
2901 Baxter Road
Ann Arbor, Michigan 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:
Bao, Shan
Feng, Fred
- Start Date: 20170101
- Expected Completion Date: 20181231
- Actual Completion Date: 20181231
- USDOT Program: University Transportation Centers Program
- Subprogram: Research
Subject/Index Terms
- TRT Terms: Automated highways; Bicycle crashes; Pedestrian movement
- Subject Areas: Research; Vehicles and Equipment;
Filing Info
- Accession Number: 01744639
- Record Type: Research project
- Source Agency: Center for Connected and Automated Transportation
- Contract Numbers: 69A3551747105
- Files: UTC, RIP
- Created Date: Jul 1 2020 11:08AM