Intelligent Transportation Systems via V2V Information: Integration of Vehicle (Powertrain), Signal Control and Adaptive Routing

Dr. Hong Wang, Oak Ridge National Laboratory

When

noon to 12:30 p.m., Nov. 17, 2023

Join in person or online:

https://arizona.zoom.us/j/5751352913

 

Hong Wang

 

Abstract: This presentation describes how the vehicle-to-vehicle V2V communications can be used to obtain optimal intelligent control effect for realizing intelligent transportation systems. The talk starts with the description of three-layered structure of the operation for transportation systems that consist of 1) vehicle-layer systems, 2) intersectional signal controls and 3) transportation management layer that looks into the adaptive routing for the system. At vehicle level, it has been shown that V2V information can be effectively used to obtain energy saving powertrain operation that leads to optimal trajectory control, where neural networks have been used to formulate equivalent energy consumption model for the optimal use of V2V information to save the fuel. At the intersection layer, a 100% Connected Autonomous Vehicle (CAV) case is given where the fault diagnosis and collaborative fault tolerant control have been applied to obtain safe operation of non-signalized intersections for CAVs to pass through the intersection. At the transportation management layer a Network-wide Intersectional Signal Control with Adaptive Routing (NISCAR) scheme is proposed that shows how the integration of vehicle (powertrain), signal control and adaptive routing can be made to provide a new and total solution to the future intelligent transportation systems.

Biography: Hong Wang (Fellows of IEEE, IET, InstMC, and AAIA received the master’s and Ph.D. degrees from the Huazhong University of Science and Technology, Wuhan, China, in 1984 and 1987, respectively. He was a Research Fellow with Salford University, Salford, U.K., Brunel University, Uxbridge, U.K., and Southampton University, Southampton, U.K., before joining the University of Manchester Institute of Science and Technology (UMIST), Manchester, U.K., in 1992. He was a Chair Professor in process control of complex industrial systems with the University of Manchester, U.K., from 2002 to 2016, where he was the Deputy Head of the Paper Science Department, the Director of the UMIST Control Systems Centre from 2004 to 2007, which is the birthplace of Modern Control Theory established in 1966. He was a University Senate member and a member of general assembly during his time in Manchester. From 2016 to 2018, he was with the Pacific Northwest National Laboratory (PNNL), Richland, WA, USA, as a Laboratory Fellow and Chief Scientist, and was the Co-Leader and the Chief Scientist for the Control of Complex Systems Initiative. He joined the Oak Ridge National Laboratory in January 2019 as a senior distinguished scientist at corporate fellow grade, US Department of Energy. He originated the stochastic distribution control theory to control the shape of the probability density functions for generic stochastic systems in 1996, and his research focuses on stochastic control, fault diagnosis and tolerant control, and intelligent controls with applications to several engineering practices including transportation system area, and has published more than 200 journal papers and 6 books together with numerous awards. He is an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems, and was an Associate Editor of the IEEE Transactions on Automatic Control, the IEEE Transactions on Control Systems Technology, and the IEEE Transactions on Automation Science and Engineering. He is also a member for three Technical Committees of International Federation of Automatic Control (IFAC).

Contacts

Henrick Haule