Dr. Ross Wang, Oak Ridge National Laboratory
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https://arizona.zoom.us/j/5751352913
Abstract: This presentation gives an overview of two recent Department of Energy (DOE) projects that utilize real-time data and artificial intelligence (AI) based modeling and control to optimize mobility systems in regional and urban settings. The presentation will discuss the design, implementation, and use cases of digital twins of Chattanooga (i.e., CTwin) and the Nimitz Highway in Honolulu, Hawaii toward the vision for smart city applications for regional and urban mobility management. Through employing AI and high performance computing (HPC) methods, both projects enable advanced capabilities for (a) real-time situational awareness on traffic and infrastructure conditions on highways and urban roads; (b) cyber-physical control for optimizing traffic signal timing; and (c) interactive visual analytics on big urban mobility data and various metrics for traffic prediction and transportation performance evaluation.
Biography: Dr. Ross Wang is the Group Leader and an R&D Staff Member in the Applied Research for Mobility Systems (ARMS) Group at ORNL. His research revolves around utilizing emerging sensing and computational technologies for transportation data collection, analysis, visualization, simulation, modeling, and application. His current research focuses on the modeling and simulation of mobility systems (i.e., vehicles and traffic) for connected and autonomous vehicles (CAVs) and smart cities applications. He leads research teams (as a PI or a co-PI) working on DOE projects with approximately $6.5 million awarded funding. He is also one of the key researchers of USDOT's national transportation data programs, including the National Household Travel Survey (NHTS) and the Freight Analysis Framework (FAF). Dr. Wang received his Ph.D. degree in Civil and Environmental Engineering from Georgia Tech and his Bachelor’s and Master’s degrees in Civil Engineering from the National Taiwan University.