文献类型：期刊文献

英文题名：A heuristic path-estimating algorithm for large-scale real-time traffic information calculating

作者：Lue WeFeng[1];Zhu TongYu[1];Wu DongDong[2];Dai Hong[3];Huang Jian[1]

第一作者：Lue WeFeng

通讯作者：Lu, WF[1]

机构：[1]Beihang Univ, State Key Lab Software Dev Environm, Beijing 100083, Peoples R China;[2]Beijing Transportat Informat Ctr, Beijing 100055, Peoples R China;[3]Beijing Union Univ, Coll Arts & Sci, Beijing 100083, Peoples R China

第一机构：Beihang Univ, State Key Lab Software Dev Environm, Beijing 100083, Peoples R China

通讯机构：[1]corresponding author), Beihang Univ, State Key Lab Software Dev Environm, Beijing 100083, Peoples R China.

年份：2008

卷号：51

期号：SUPPL. 1

起止页码：165-174

外文期刊名：SCIENCE IN CHINA SERIES E-TECHNOLOGICAL SCIENCES

收录：;EI(收录号：20082511323447);Scopus(收录号：2-s2.0-44949244266);WOS:【SCI-EXPANDED(收录号:WOS:000256309100017)】；

基金：Received December 10, 2007; accepted January 12, 2008 doi: 10.1007/s11431-008-5013-6 ?Corresponding author (email: lwf@nlsde.buaa.edu.cn) Supported by the National Basic Research Program of China (“973”) (Grant No. 2005CB321900) and the National Hi-Tech Research and Development Program of China (Grant No.2006AA12Z315)

语种：英文

外文关键词：path-estimating; floating car data (FCD); road network vector; GPS

摘要：As the original Global Position System (GPS) data in Floating Car Data have the accuracy problem, this paper proposes a heuristic path-estimating algorithm for large-scale real-time traffic information calculating. It uses the heuristic search method, imports the restriction with geometric operation, and makes comparison between the vectors composed of the vehicular GPS points and the special road network model to search the set of vehicular traveling route candidates. Finally, it chooses the most optimal one according to weight. Experimental results indicate that the algorithm has considerable efficiency in accuracy (over 92.7%) and computational speed (max 8000 GPS records per second) when handling the GPS tracking data whose sampling rate is larger than 1 min even under complex road network conditions.