With the increase of urban residents' population, the urban public transportation system faces new challenges. As an important transportation mode to satisfy residents' spatial and temporal needs, the mining of the operation characteristics of taxis is of great significance to understand the urban travel pattern and reduce the cost of the transportation system. Based on the taxi trajectory data in Chengdu, this study fuses electronic maps and GPS positioning data, firstly, the GPS data are trajectorized, then the trajectory data are matched with road network maps for OD maps, and finally, the operating time and distance characteristics of taxis are explored. It is found that taxi trips tend to be short duration and short distance trips, especially trips within 15 minutes and 3 kilometers. The taxi operation characteristics mining in this paper provides valuable references for urban transportation planning and taxi operation management.


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    Titel :

    Mining urban taxi operation characteristics based on spatio-temporal trajectory data


    Beteiligte:
    Wu, Jinsong (Herausgeber:in) / Ma'aram, Azanizawati (Herausgeber:in) / Kugan, Huang (Autor:in) / Huan, Xiong (Autor:in) / Chun, Bao (Autor:in) / Jianqiu, Chen (Autor:in) / Shiyu, Wang (Autor:in) / Lou, Benxiao (Autor:in) / Jiayu, Sun (Autor:in) / Chujie, Zhong (Autor:in)

    Kongress:

    Ninth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2024) ; 2024 ; Guilin, China


    Erschienen in:

    Proc. SPIE ; 13251


    Erscheinungsdatum :

    28.08.2024





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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