Title | How could the station-based bike sharing system and the free-floating bike sharing system be coordinated? |
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Type | Journal article |
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Authors | Cheng, L., Yang, J., Chen, X., Cao, M., Zhou, H. and Sun, Y. |
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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. |
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Keywords | Station-based bike sharing system |
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| Free-floating bike sharing system |
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| Support vector machine |
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| Coordinated development |
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| Land use |
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Article number | 102896 |
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Journal | Journal of Transport Geography |
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Journal citation | 89 |
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ISSN | 0966-6923 |
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Year | 2020 |
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Publisher | Elsevier |
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Accepted author manuscript | License CC BY-NC-ND 4.0 File Access Level Open (open metadata and files) |
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Digital Object Identifier (DOI) | https://doi.org/10.1016/j.jtrangeo.2020.102896 |
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Web address (URL) | https://www.sciencedirect.com/science/article/pii/S096669232030973X?dgcid=coauthor |
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Publication dates |
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Published | 20 Oct 2020 |
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Published in print | Dec 2020 |
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