Research on intelligent traffic light control system based on dynamic Bayesian reasoning

doi:10.1016/j.compeleceng.2020.106635

	Research on intelligent traffic light control system based on dynamic Bayesian reasoning
	Xiao Zhengxing 1; Jiang Qing 2; Nie Zhe 1; Wang Rujing 2; Zhang Zhengyong 2; Huang He 2; Sun Bingyu 2; Wang Liusan 2; Wei Yuanyuan 2
刊名	COMPUTERS & ELECTRICAL ENGINEERING
	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
DOI	10.1016/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.
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关键词	NETWORKS
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号	WOS:000579053300006
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
内容类型	期刊论文
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).