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Apr 26, 2012
Reinforcement Learning Ramp Metering Based on Traffic Simulation Model with Desired Speed
Authors: Xingju Wang [email protected], Jingang Bao [email protected], Mingsheng Wang, and Toshihiko Miyagi [email protected]Author Affiliations
Publication: International Conference on Transportation Engineering 2009
Abstract
Since generation of the traffic congestion in a highway brings about an efficiency fall of road operation as well as an increase in energy consumption and environmental pollution, various kinds of traffic control have been considered for easing traffic congestion until now. In this paper, reinforcement learning is introduced. By combining this model with a simulation model for describing the traffic flow behavior in the merging sections in highways, a novel reinforcement learning ramp metering is proposed. By numerical simulation experiments, this model showed that the effect of the proposed control measure is large in the highway.
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International Conference on Transportation Engineering 2009
Pages: 3184 - 3189
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© 2009 American Society of Civil Engineers.
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Published online: Apr 26, 2012
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Affiliations
School of Traffic and Transportation, Shijiazhuang Railway Institute, P.O. Box 050043, Shijiazhuang, Hebei, China Email: [email protected] and Traffic Safety and Control Laboratory of Hebei Province, P.O. Box 050043, Shijiazhuang, Hebei, China. E-mail: [email protected]
Graduate, School of Engineering, Gifu University, P.O. Box 5011193, Gifu, Japan. E-mail: [email protected]
Mingsheng Wang
School of Traffic and Transportation, Shijiazhuang Railway Institute, P.O. Box 050043, Shijiazhuang, Hebei, China and Traffic Safety and Control Laboratory of Hebei Province, P.O. Box 050043, Shijiazhuang, Hebei, China
Graduate, School of Information Sciences, Tohoku University, P.O. Box 9808578, Sendai, Japan. E-mail: [email protected]
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