A Fusion Model for Multi-source Detect Data of Section Average Velocity Based on BP Network

摘要：

　　As section average velocity that is one of the most important traffic flow parameters has a wide range of sources of data,different sources of data vary in standards,advantages and disadvantages.Single-detect equipment can’t meet the needs of multi-purpose and different environments.What’s more,under certain conditions,the detector performance is defective,and it can’t get rich and high-quality section average velocity information.The paper will try to use B-P neural network to do date fusion,to get more realistic traffic flow speed information,to provide a basis for traffic management,control,and induction measures.Taking Beijing as the research background,the expressway section average velocity of multi-source data is adopted to do data fusion in the final section of the study.

关键词： Freeway Section average velocity B-P neural network Data fusion

作者: Dong Honghui Wu Mingchao Jin Maojing Zhang Pengfei Zhang Yu Jia Limin Qin Yong

作者单位: State Key Laboratory of Rail Traffic Control & Safety, Beijing Jiaotong University, Beijing 100044 The High Technology Research & Development Center ,The Ministry of Science & Technology, Beijing 100

会议类型: 国际会议

会议名称: the 25th Chinese Control and Decision Conference(第25届中国控制与决策会议)

会议地点: 贵阳

会议语种:英文

页码: 2198-2203

在线出版日期: 2013-05-01（万方平台首次上网日期，不代表论文的发表时间）