Toward Ubiquitous Trajectory‐Based Traffic Network Diagnosis Systems
This project aims to develop a trajectory-based traffic network diagnosis system to address urban congestion by leveraging vehicle trajectory data and open-source tools. The system operates at both planning and operational levels, offering scalable, real-time diagnosis and mitigation of congestion issues. It integrates advanced equilibrium models and mesoscopic simulations, prioritizing computational efficiency and actionable results. By democratizing access to traffic diagnostics and enabling rapid deployment, the project envisions empowering cities worldwide to manage congestion sustainably, enhance urban mobility, and improve quality of life.
Language
- English
Project
- Status: Active
- Funding: $150,000.00
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Contract Numbers:
69A3552348305
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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:
University of Michigan Transportation Research Institute
2901 Baxter Road
Ann Arbor, Michigan United States 48109 -
Project Managers:
Bezzina, Debra
Stearns, Amy
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Performing Organizations:
University of Michigan, Ann Arbor
Department of Civil and Environmental Engineering
2350 Hayward
Ann Arbor, MI United States 48109-2125 -
Principal Investigators:
Yin, Yafeng
Liu, Henry
- Start Date: 20251015
- Expected Completion Date: 20261015
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Congestion management systems; Connected vehicles; Mesoscopic traffic flow; Traffic simulation; Vehicle trajectories
- Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment;
Filing Info
- Accession Number: 01970972
- Record Type: Research project
- Source Agency: Center for Connected and Automated Transportation
- Contract Numbers: 69A3552348305
- Files: UTC, RIP
- Created Date: Nov 13 2025 4:01PM