[2017-05-11] Dr. Hsu-Chieh Hu, CMU," Scalable urban traffic control: How can dynamic automation of traffic lights improve urban mobility and lower emission?”

Title: Scalable urban traffic control: How can dynamic automation of traffic lights improve urban mobility and lower emission? 
Date: 2017-05-11 2:20pm-3:30pm
Location: R103, CSIE
Speaker: Dr. Hsu-Chieh Hu, CMU
Hosted by: Prof. Hsin-Mu Tsai


Recent work in decentralized, schedule-driven traffic control has demonstrated the ability to improve the efficiency of traffic flow in complex urban road networks. In this approach, a scheduling agent is associated with each intersection. Each agent senses the traffic approaching its intersection and in real-time constructs a schedule that minimizes the cumulative wait time of vehicles approaching the intersection over the current look-ahead horizon. In order to achieve network level coordination in a scalable manner, scheduling agents communicate only with their direct neighbors. Each time an agent generates a new intersection schedule it communicates its expected outflows to its downstream neighbors as a prediction of future demand and these outflows are appended to the downstream agent's locally perceived demand. This talk focuses on two aspects of schedule-driven traffic control: stability and optimality. For stability, we propose a hybrid approach that incorporates the stability of queuing theory into a schedule-driven control framework.  For optimality, the basic coordination protocol is extended to additionally incorporate the complementary flow of information reflective of an intersection's current congestion level to its upstream neighbors. We propose an asynchronous decentralized algorithm in order to approach network-wide optimality. In addition, we will discuss what’s next for the system, including better optimization with buses and autonomous vehicles, and self-learnability of system.



Hsu-Chieh Hu is currently a Ph.D. candidate in Department of Electrical and Computer Engineering and Robotics Institute at Carnegie Mellon University (CMU). His research focuses on planning, optimization, reinforcement learning and their applications in transportation. Prior to CMU, he was a software engineer at MediaTek, Taiwan from 2010 to 2013. He received the B.S.E. degree in electrical engineering in 2008, and M.S. degree in communication engineering in 2010, both from National Taiwan University, Taipei, Taiwan.


最後修改時間:2018-04-25 PM 3:02

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