Edge Computing for Safer and Smarter Transportation Applications
Sensors are essential for the intelligence needed by smart cities, particularly smart transportation applications, and have been increasingly deployed over the past decade. Although these sensors are capable of collecting a substantial amount of data, the bandwidth and cost constraints of the communication network may not allow all these data to be transferred for timely processing on the cloud or server. Thus it is highly desirable to process, store, and extract data at the edge where things and people produce or consume the data, and this has led to a new research field called edge computing. Due to the limited computing power at the edge devices (such as the sensors), however, conventional computation models, particularly artificial intelligence (AI) methods, cannot be directly applied. To address this challenge, research efforts are needed to develop new methods and tools for efficient data processing, analysis, and understanding. This talk intended to introduce a couple of such research efforts made at the University of Washington Smart Transportation Applications and Research Laboratory (STAR Lab) that produced example edge computing methods, including edge AI, for safer and smarter transportation applications. The superb performance of these edge computing methods clearly indicates the value of such research efforts. Hopefully, this presentation will stimulate more researchers to invest their energy in edge computing methods and tools for improved transportation safety and system operations.
Dr. Yinhai Wang is a professor in transportation engineering at Civil and Environmental Engineering and an adjunct professor at Electrical and Computer Engineering of the University of Washington (UW). He is also the founding director of the UW Smart Transportation Applications and Research Laboratory (STAR Lab) and has served as director for Pacific Northwest Transportation Consortium (PacTrans), USDOT University Transportation Center for Federal Region 10, since 2012. Dr. Wang was the 2018-2019 president of the Transportation & Development Institute at the American Society of Civil Engineers (ASCE). His active research fields include traffic sensing, transportation safety, transportation data science, big-data analytics, traffic operations and simulation, smart urban mobility, etc. He has published over 230 peer-reviewed journal articles and delivered more than 190 invited talks and nearly 300 other academic presentations. Also, he serves as a member of the Artificial Intelligence and Advanced Computing Committee of the Transportation Research Board (TRB), IEEE Smart Cities Technical Activity Committee, and associate editor for two journals, including the Journal of Transportation Engineering Part A and Journal of Intelligent Transportation Systems. He was the winner of the ASCE Journal of Transportation Engineering Best Paper Award for 2003, IEEE International Smart Cities Conference’s Best Paper Award for 2020, and Institute of Transportation Engineers (ITE) Innovation in Education Award for 2018.