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Neural network based online traffic signal controller design with reinforcement training (EI CONFERENCE)

文献类型：会议论文

作者Dai Y. ; Hu J. ; Zhao D. ; Zhu F.
出版日期2011
会议名称14th IEEE International Intelligent Transportation Systems Conference, ITSC 2011, October 5, 2011 - October 7, 2011
会议地点Washington, DC, United states
关键词Traffic congestion leads to problems like delays decreasing flow rate and higher fuel consumption. Consequently keeping traffic moving as efficiently as possible is not only important to economy but also important to environment. Traffic system is a large complex nonlinear stochastic system. Traditional mathematical methods have some limitations when they are applied in traffic control. Thus computational intelligence (CI) technologies gain more and more attentions. Neural Networks (NNs) is a well developed CI technology with lots of promising applications in traffic signal control (TSC). In this paper a neural network (NN) based signal controller is designed to control the traffic lights in an urban traffic road network. Scenarios of simulation are conducted under a microscopic traffic simulation software. Several criterions are collected. Results demonstrate that through online reinforcement training the controllers obtain better control effects than the widely used pre-time and actuated methods under various traffic conditions. 2011 IEEE.
页码1045-1050
收录类别EI
源URL[http://ir.ciomp.ac.cn/handle/181722/32951]  
专题长春光学精密机械与物理研究所_中科院长春光机所知识产出_会议论文
推荐引用方式
GB/T 7714		 Dai Y.,Hu J.,Zhao D.,et al. Neural network based online traffic signal controller design with reinforcement training (EI CONFERENCE)[C]. 见:14th IEEE International Intelligent Transportation Systems Conference, ITSC 2011, October 5, 2011 - October 7, 2011. Washington, DC, United states.

入库方式： OAI收割

来源：长春光学精密机械与物理研究所

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