The taxi is a common way of travelling in cities, which is an important supplement to other public travel modes. Thus, it is necessary to understand the characters of taxi operation and its passengers. The individual vehicle trajectory information has been obtained easily and economically because of the widely-used GPS devices, which makes mining the meaningful information behind the trajectory feasible and more convenient. In this paper, the taxi GPS data from Kunshan City, in China, is used to identify the pick-up and drop-off hotspots. Firstly, a procedure is proposed to extract the taxi trip trajectories from the vast amounts of GPS data. Then, with the help of data mining technology, the pick-up and drop-off hotspots are analyzed using the density-based spatial clustering method. It comes to a conclusion that the pick-up and drop-off hotspots can share a similar distribution pattern and overlap very well.


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    Titel :

    Identification of Taxi Pick-Up and Drop-Off Hotspots Using the Density-Based Spatial Clustering Method


    Beteiligte:
    Zhou, Dong (Autor:in) / Hong, Rongrong (Autor:in) / Xia, Jingxin (Autor:in)

    Kongress:

    17th COTA International Conference of Transportation Professionals ; 2017 ; Shanghai, China


    Erschienen in:

    CICTP 2017 ; 196-204


    Erscheinungsdatum :

    18.01.2018




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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