文章基本信息

标题：THE TAXIS' EXPERIENCE KNOWLEDGE MODELING AND ROUTE PLANNING
本地全文：下载
作者：Tang Luliang ; Li Qingquan ; Chang Xiaomeng 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2009
卷号：XXXVIII-4/W10
出版社：Copernicus Publications
摘要：It is believed that the routes chosen by taxi drivers are more reasonable than regular drivers, and the dynamic navigation based on real-time traffic information is not mature both in the software and hardware fields, and the real-time data acquisition, data processing and communication need to be improved, and short-term traffic forecast in large area is still not accurate enough to route planning. So, it is important to plan the route using taxi drivers' experience and knowledge. This paper establishes a taxis' experience knowledge model (TEKM) based on analyzing historical floating car data (FCD) and taxi drivers' planning route rules. The road network is classified into different experience levels network, and a new route planning algorithm is proposed based on TEKM. In the end, we conducted 350 experiments with the road network and historical FCD of Wuhan, and compared the TEKM with the traditional shortest path algorithm. The results show us that the routes planed by TEKM are more coherent and consistent, and that the travelling time can be reduced
关键词：floating car data (FCD); TEKM; route planning; GIS-T