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论文类型：会议论文

发表时间：2016-12-12

收录刊物：EI

卷号：10086 LNAI

页面范围：811-814

摘要：Intelligent transportation systems (ITSs) became an essential tool for a broad range of transportation applications. Traffic flow visualization is an important problem in ITS. The visualized results can be used to support ITSs to plan operation and manage revenue. In this paper, we aim to visualize the daily floating taxis by presenting a novel figure using taxi trajectory data and weather information. Many visualization platforms feature a online-offline phase, in which taxi GPS trajectory data is processed by two phases. This approach incurs high costs though, since trajectory data is huge generated by taxis every second continually. To support the frequent trajectories, we present an analysis tool for mining frequent trajectories of taxis (FTMTool). It allows us to find the driver’s routes by collecting input on the most frequent roads, thereby achieving a set of high quality routes. The tool also supports the task statistic in selecting the specific roads. We demonstrate the usefulness of our tool using real data from New York city. © Springer International Publishing AG 2016.