In this paper, we seek to identify the different impacts of external and internal information on taxis’ cruising behaviors and to find effective methods to enhance taxis’ cruising efficiency. Through global positioning system trajectory data collected in Shenzhen, China, we determine the impacts of external factors (land use, traffic conditions, and road grade) and internal factors (previous pick-up experience) on cruising location choice using a zero-inflated negative binomial model. The results indicate that the external factors have a more significant influence than the internal ones. Specifically, traffic conditions, land use, urban expressways, and previous pick-up points are the major factors that influence drivers’ cruising decisions. The results also show that drivers follow different patterns during different times of day, i.e., relying on traffic conditions and land use in the morning/ evening peak hours but emphasizing land use and previous pick-up experience during non-peak hours. In addition, high-earning drivers and roaming drivers prefer to cruise in areas with high-density land use and optimal traffic conditions, whereas low-earning drivers and target drivers tend to cruise in areas with more previous pick-up points. These findings uncover the underlying mechanisms of cruising decisions and facilitate the development of strategies to minimize empty cruising time. Based on the study results, the external and internal information that was found to affect cruising decisions can be released to taxi drivers to improve their cruising efficiency. This information is also helpful to managers in deciding the overall layout of taxi service locations.


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    Titel :

    Taxi Drivers’ Cruising Patterns—Insights from Taxi GPS Traces


    Beteiligte:
    Zong, Fang (Autor:in) / Wu, Ting (Autor:in) / Jia, Hongfei (Autor:in)


    Erscheinungsdatum :

    2019-02-01


    Format / Umfang :

    4709409 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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