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Title	Reinforcement Learning For Traffic Signal Timing Optimization
ID_Doc	44887
Authors	Joo H.; Lim Y.
Year	2020
Published	International Conference on Information Networking, 2020-January
DOI	http://dx.doi.org/10.1109/ICOIN48656.2020.9016568
Abstract	A smart city has being studied to improve the quality of life. A traffic control system is a part of what smart cities need to deal with. The traffic control system identifies the traffic flow and controls the vehicle at an intersection. This study proposes a traffic signal control system that uses Q-learning to maximize throughput and minimize waiting time. The proposed system has optimized traffic signals by adjusting the time of the green signal and allocating the green signal. We conducted an experiment by applying two kinds of traffic load. The performance is also analyzed by applying data with urban traffic density distribution. © 2020 IEEE.
Author Keywords	Q-learning; throughput; traffic congestion; traffic signal control; waiting time

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