Abstract The station-based bike sharing system (SBBSS) and the free-floating bike sharing system (FFBSS) have been adopted on a large scale in China. However, the overlap between the services provided by these two systems often makes bike sharing inefficient. By comparing the factors that affect the usage of the two systems, this paper aims to propose appropriate strategies to promote their coordinated development. Using data collected in Nanjing, a predictive model is built to determine which system is more suitable at a given location. The influences of infrastructure, demand distribution, and land use attributes at the station level are examined via the support vector machine (SVM) approach. Our results show that the SBBSS tends to be favored in areas where there is a high concentration of travel demand, and close proximity to metro stations and commercial properties, whereas locations with a higher density of major roads and residential properties are associated with more frequent use of the FFBSS. With regard to the methods used, a comparison of several machine learning approaches shows that the SVM has the best predictive performance. Our findings could be used to help policy makers and transportation planners to optimize the deployment and redistribution of docked and dockless bikes.

    Highlights The coordinated development of docked and dockless bike sharing schemes can be achieved. SBBSS is favored in places with a concentration of demand and near metro stations and commercial properties. FFBSS is frequently used in places with a higher density of major roads and residential properties. Support vector machine produces the best predictive performance.


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    Title :

    How could the station-based bike sharing system and the free-floating bike sharing system be coordinated?


    Contributors:
    Cheng, Long (author) / Yang, Junjian (author) / Chen, Xuewu (author) / Cao, Mengqiu (author) / Zhou, Hang (author) / Sun, Yu (author)


    Publication date :

    2020-10-16




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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