Analysis of spatiotemporal trajectories for stops along taxi paths |
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| Authors: | Liang Huang Yuanqiao Wen Chunhui Zhou Faming Zhang Jay Lee |
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| Institution: | 1. Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, China;2. School of Navigation, Wuhan University of Technology, Wuhan, China;3. Hubei Key Laboratory of Inland Shipping Technology, Wuhan, China;4. National Engineering Research Center for Water Transport Safety, Wuhan, China;5. School of Navigation, Wuhan University of Technology, Wuhan, China;6. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China;7. Department of Geography, Kent State of Univeristy, Kent, USA |
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| Abstract: | Stops along taxi trajectories, such as picking up and dropping off passengers, are spatially clustered and related to certain attributes of places where stops are made. To detect the hidden knowledge regarding these places, this article examines the semantics of massive taxi stops in a large city. Each taxi trajectory is modeled as a series of sequential semantic stops labeled by street names. All the trajectories can be examined as a document corpus, from which the hidden themes of the stops are identified through Latent Dirichlet Allocation model. Conventional GIS tools are coupled with topic modeling toolkit to visualize and analyze potential information of stop topics for understanding intra-city dynamics. The effectiveness of this approach is illustrated by a case study using a large dataset of taxi trajectories including approximately 4,000 taxis in Wuhan, China. |
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| Keywords: | semantic trajectory analysis topic modeling taxi human dynamics China |
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