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《Journal of Transport Information and Safety》 2013-06
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Multi-step Short-term Traffic Flow Prediction Based on Chaotic Theory

JIA Xianchao;CHEN Xumei;GONG Jinli;Zhang Xi;GUO Shuxia;MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University;School of Traffic and Transportation Engineering,Changsha University of Science and Technology;Beijing Transportation Research Center;Department of Transportation Research Center,Beijing Municipal Engineering Design and Research Institute;  
Short-term traffic flow prediction is one of the key issues in intelligent transportation system studies. Through considering the chaotic characteristics of urban traffic flow,a method with high accuracy of multi-step shortterm traffic flow prediction is proposed to support the traffic control and route guidance.The chaotic characteristics of traffic flow time series can be distinguished by using the largest Lyapunov exponent method.Then,the phase space reconstruction of traffic flow time series is conducted.On this basis,multi-step traffic flow prediction algorithm is designed based on chaotic theory by further using adding-weight one-rank local-region method.The proposed traffic flow prediction algorithm is applied to a case study,and the multi-step predicted values are compared with the real traffic flow value.The results show that the proposed algorithm has a high accuracy with the mean absolute percentage error 3.33%,the mean absolute error 9.05,and the root mean square error 10.36.
【Fund】: 国家重点基础研究发展计划项目(批准号:2012CB725403);; 国家自然科学基金项目(批准号:71373018、T13L00450);; 新世纪优秀人才支持计划项目(批准号:NCET-12-0763)资助
【CateGory Index】: U491.112
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