Traffic light optimization is known to be a cost-effective method for reducing congestion and energy consumption in urban areas without changing physical road infrastructure. However, due to the high installation and maintenance costs of vehicle detectors, most intersections are controlled by fixed-time traffic signals that are not regularly optimized. To alleviate traffic congestion at intersections, Dr. Liu’s team presents a large-scale traffic signal re-timing system that uses a small percentage of vehicle trajectories as the only input without reliance on any detectors. A probabilistic time-space diagram has been developed, which establishes the connection between a stochastic point-queue model and vehicle trajectories under the proposed Newellian coordinates. This model enables the team to reconstruct the recurrent spatial-temporal traffic state by aggregating sufficient historical data. Optimization algorithms are then developed to update traffic signal parameters for intersections with optimality gaps. A real-world citywide test of the system was conducted in Birmingham, MI, and demonstrated that it decreased the delay and number of stops at signalized intersections by up to 20% and 30%, respectively. This system provides a scalable, sustainable, and efficient solution to traffic light optimization and can potentially be applied to every fixed-time signalized intersection in the world.
---
About the speaker: Dr. Henry Liu is the Bruce D. Greenshields Collegiate Professor of Engineering and the Director of Mcity at the University of Michigan, Ann Arbor. He is a Professor of Civil and Environmental Engineering, a Professor of Mechanical Engineering, and a Research Professor at the University of Michigan Transportation Research Institute. He also directs the Center for Connected and Automated Transportation, a USDOT-funded regional university transportation center. Dr. Liu conducts interdisciplinary research at the interface of transportation engineering, automotive engineering, and artificial intelligence. He is recognized for his foundational work in cyber-physical transportation systems, particularly on the development of smart traffic signal systems with connected vehicles, and testing/evaluation of autonomous vehicles. He has published more than 140 refereed journal articles. His work on safety validation of autonomous vehicles has been published in Nature and featured as the cover story. He has also appeared on a number of media outlets including Wall Street Journal, Forbes, Science Daily, Tech Xplore, CNBC, WXYZ, etc. for transportation innovations. Prof. Liu is the managing editor of the Journal of Intelligent Transportation Systems and a board member of the ITS America and IEEE ITS Society.