中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Research on intelligent traffic light control system based on dynamic Bayesian reasoning

文献类型:期刊论文

作者Xiao Zhengxing1; Jiang Qing2; Nie Zhe1; Wang Rujing2; Zhang Zhengyong2; Huang He2; Sun Bingyu2; Wang Liusan2; Wei Yuanyuan2
刊名COMPUTERS & ELECTRICAL ENGINEERING
出版日期2020-06-01
卷号84
关键词Intelligent traffic light Dynamic Bayesian network Intelligent decision model Dynamic Bayesian reasoning
ISSN号0045-7906
DOI10.1016/j.compeleceng.2020.106635
通讯作者Jiang Qing(jiangqing@iim.ac.cn)
英文摘要Intelligent traffic lights are an important part of intelligent transportation systems. In this paper, the Bayesian network theory is used to establish a traffic light independent intelligent decision model based on dynamic Bayesian network. According to the real-time dynamic information of traffic conditions, the proposed dynamic Bayesian network approximate reasoning algorithm is used to realize online reasoning and determine the best traffic light time. The algorithm combines the time window with the improved forward-backward algorithm. By adjusting the time window width of the algorithm, the evidence information can be used to maximize online reasoning. Compared with the existing time window based on interface algorithm, it's proved that the reasoning algorithm proposed is more efficient. The research results of this paper have important practical significance in solving the traffic congestion problem and reducing the waiting time of people at the intersection of traffic lights. (C) 2020 Elsevier Ltd. All rights reserved.
WOS关键词NETWORKS
资助项目Thirteenth Five-Year National Key Research and Development Program of China[2016YFD0702002] ; Thirteenth Five-Year National Key Research and Development Program of China[2016YFD0702001] ; Thirteenth Five-Year National Key Research and Development Program of China[2016YFD0702003] ; Thirteenth Five-Year National Key Research and Development Program of China[2017YFD0700705-3] ; Thirteenth Five-Year National Key Research and Development Program of China[2017YFD0700501] ; Department of Education of GuangDong Province, PRC[2017GKTSCX060] ; National Natural Science Foundation of China[61773360] ; National Natural Science Foundation of China[61863013] ; National Natural Science Foundation of China[61503362] ; National Natural Science Foundation of China[61305111] ; National Natural Science Foundation of China[31671586] ; National Natural Science Foundation of China[91420104] ; Natural Science Foundation of Anhui Province[1508085MF133] ; Key Technology and Equipment Research and Development of Intelligent Harvest of Chinese wolfberry with high efficiency and low loss[nxzdkjxm2016-04] ; Research and application of soil fertility rapid sensing device and large data fertilization model[15czz03129] ; Research of Agricultural Science and Technology in Ningxia[XD-XMBW-2016001] ; Construction of test and maturation platform for complete sets of hardware and software in Agricultural Internet of things (Shanghai agriculture promotion word (2016))[2-5-11] ; Natural key projects of the Department of Education of Anhui Province[KJ2016A305]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000579053300006
出版者PERGAMON-ELSEVIER SCIENCE LTD
资助机构Thirteenth Five-Year National Key Research and Development Program of China ; Department of Education of GuangDong Province, PRC ; National Natural Science Foundation of China ; Natural Science Foundation of Anhui Province ; Key Technology and Equipment Research and Development of Intelligent Harvest of Chinese wolfberry with high efficiency and low loss ; Research and application of soil fertility rapid sensing device and large data fertilization model ; Research of Agricultural Science and Technology in Ningxia ; Construction of test and maturation platform for complete sets of hardware and software in Agricultural Internet of things (Shanghai agriculture promotion word (2016)) ; Natural key projects of the Department of Education of Anhui Province
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/104606]  
专题中国科学院合肥物质科学研究院
通讯作者Jiang Qing
作者单位1.Shenzhen Polytech, Sch Comp & Engn, Shenzhen 518055, Peoples R China
2.Chinese Acad Sci, Inst Intelligent Machines, Hefei 230031, Peoples R China
推荐引用方式
GB/T 7714
Xiao Zhengxing,Jiang Qing,Nie Zhe,et al. Research on intelligent traffic light control system based on dynamic Bayesian reasoning[J]. COMPUTERS & ELECTRICAL ENGINEERING,2020,84.
APA Xiao Zhengxing.,Jiang Qing.,Nie Zhe.,Wang Rujing.,Zhang Zhengyong.,...&Wei Yuanyuan.(2020).Research on intelligent traffic light control system based on dynamic Bayesian reasoning.COMPUTERS & ELECTRICAL ENGINEERING,84.
MLA Xiao Zhengxing,et al."Research on intelligent traffic light control system based on dynamic Bayesian reasoning".COMPUTERS & ELECTRICAL ENGINEERING 84(2020).

入库方式: OAI收割

来源:合肥物质科学研究院

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