详情

原文传递 NN-based Link Travel Time Estimation: Modeling and Analysis

题名：	NN-based Link Travel Time Estimation: Modeling and Analysis
正文语种：	中文
作者：	WANG Wei-feng ONG Xue-wu JI Jin-zhang ING Shan-shan
作者单位：	ITS Research enter,Jiangsu Transportation Planning and esign Institute o.,Ltd.,Nanjing Jiangsu 210014, hina;Research and evelopment enter of ITS Technology and Equipment,Ministry of Transport,Nanjing Jiangsu 210014, hina;School of Transportation,Southeast University,Nanjing Jiangsu 210009, hina ITS Research enter,Jiangsu Transportation Planning and esign Institute o.,Ltd.,Nanjing Jiangsu 210014, hina;Research and evelopment enter of ITS Technology and Equipment,Ministry of Transport,Nanjing Jiangsu 210014, hina
关键词：	ITS link travel time neural network multi-source data fusion
摘要：	Estimating link travel time in a reasonable fashion based on multi-source data is becoming a major challenge for intelligent transportation system (ITS).In this study, five crucial parameters from multi-source data (i.e.data from fixed sensors and probe vehicles) were proposed by analyzing their impacts on link travel time.As a typical multisource data fusion (MDF) method, a three-layer Back-propagation Neural Network (BPNN) model was developed to estimate link travel time using different combinations of the proposed parameters as the model's input vectors.To validate the BPNN model, estimated link travel time was compared to simulated link travel time obtained by Vissim-based experiments.Results showed that the developed model has good performance in time estimation, and reasonable input parameters of the model could improve estimation accuracy and constancy.
会议日期：	20150427
会议举办地点：	南京
会议名称：	2015年南京第十四届亚太智能交通论坛
出版日期：	2015-04-27
母体文献：	2015年南京第十四届亚太智能交通论坛论文集