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原文传递 A decentralized intersection management system through collaborative negotiation between smart signals

题名：	A decentralized intersection management system through collaborative negotiation between smart signals
正文语种：	eng
作者：	Russell T. Graves;Zachariah E. Nelson;Subhadeep Chakraborty
作者单位：	Department of Mechanical Engineering University of Tennessee Knoxville TN USA;Department of Mechanical Engineering University of Tennessee Knoxville TN USA;Department of Mechanical Engineering University of Tennessee Knoxville TN USA
关键词：	Decentralization; distributed control; intelligent agents; intelligent control systems; signalized intersections
摘要：	Actuated and pre-timed traffic signal controllers have been beneficial to the improvement of traffic flow in cities and dense urban environments around the world. While these methods have been effective in reducing traffic congestion, recent works have shown that incorporation of reinforcement learning (RL) or other artificial intelligence (Al) based optimization techniques may further improve the performance of traffic signal controllers. This work investigates a novel decentralized traffic signal control structure which encourages cooperative signal behavior via repeated negotiations between neighboring intelligent agents. This method capitalizes on emerging inter-infrastructure communications technologies to exercise 'system-level' control over a network of connected signalized intersections. The proposed method was tested in a simplified grid-network of 20 intersections. In this network, static arrivals of 1440 veh/l/h along east-west lanes and 360 veh/l/h along north-south lanes were supplied. In addition, a simulated shift to 720 veh/l/h along east-west lanes and 1080 veh/l/h along north-south lanes was analyzed to provide insights into the presented method's performance in response to any sudden shifts in traffic patterns. The findings indicated that, when compared to non-negotiating traffic signals, the presented method may improve the service rate of traffic networks under static conditions by 671 veh/h on average, reduce emissions by an average of 326 kg/h in addition to reducing travel time across a network of intersections. The performance characteristics were captured by a SUMO testbed, and computational efficiency was explored using a suite of simple test-beds developed in MATLAB.
出版年：	2023
期刊名称：	Journal of Intelligent Transportation Systems
卷：	27
期：	1/6
页码：	272-294