Traffic signs are critical assets for roadway and infrastructure management. They are also in a great variety and different conditions....
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Yinhai Wang
Professor, University of Washington
Dr. Yinhai Wang is a professor in transportation engineering and the founding director of the Smart Transportation Applications and Research Laboratory (STAR Lab) at the University of Washington (UW). He also serves as director for Pacific Northwest Transportation Consortium (PacTrans), USDOT University Transportation Center for Federal Region 10 and visiting chair for the Traffic Information and Control Department at Harbin Institute of Technology. He has a Ph.D. in transportation engineering from the University of Tokyo (1998), a master’s degree in computer science from the UW, and another master’s degree in construction management (1991) and a bachelor’s degree in civil engineering (1989) from Tsinghua University in China. Dr. Wang’s active research fields include traffic sensing, e-science of transportation, big-data analytics, traffic operations and simulation, smart urban mobility, transportation safety, etc. He has published over 120 peer reviewed journal articles and delivered more than 130 invited talks and nearly 220 other academic presentations.
C2SMART Projects
Research and Field Testing of Vehicle-Traffic Control with Limited-Capacity Connected/Automated Vehicles
This project aims to extend and field-test CAV-based traffic signal/vehicle control methods developed by the research team in previous projects...
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An Artificial Intelligence Platform for Network-wide Congestion Detection and Prediction Using Multi-source Data
The research team has already established an online transportation platform, named the Digital Roadway Interactive Visualization and Evaluation Network (DRIVE...
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Modeling and Optimizing Ridesourcing Services in Connected and Automated Cities
This research aims to develop modeling and analysis methods to capture the key behaviors and intersections of the major players...
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Cooperative Perception of Road-Side Unit and Onboard Equipment with Edge Artificial Intelligence for Driving Assistance
Although lots of research have been conducted on multi-vehicle cooperative perception, few studies have considered combining information from vehicle onboard...
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A Multiscale Simulation Platform for Connected and Automated Transportation Systems
Traffic simulation is an important tool that can assist researchers, analysts, and policymakers to test vehicle/traffic control algorithms, gain insights...
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Integrative Vehicle-Traffic Control in Connected/Automated Cities
In this project, the research team built on work done in a Year 1 C2SMART project, in which a decomposition...
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