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Dynamic Rebalancing of the Free-Floating Bike-Sharing System

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  • Wenbin Zhang

    (School of Mathematical Sciences, Jiangsu Second Normal University, Nanjing 210013, China)

  • Xiaolei Niu

    (School of Mathematical Sciences, Jiangsu Second Normal University, Nanjing 210013, China)

  • Guangyong Zhang

    (Faculty of science, Wuxi University, Wuxi 214105, China)

  • Lixin Tian

    (Energy Development and Environmental Protection Strategy Research Center, Jiangsu University, Zhenjiang 212013, China
    School of Mathematical Sciences, Nanjing Normal University, Nanjing 210023, China)

Abstract

In the paper, we propose a novel method to analyze the rebalancing of the free-floating bike-sharing system. First, we construct a visualization method to analyze the rebalancing of the system. Then, for the first time, we set up a coarse-grained way to study dynamics rebalancing during rush hours. Finally, we complete the empirical analysis with the real-time cycling data of the Nanjing Mobike Sharing-bike Company. The results show that: static rebalancing is weak, and dynamic rebalancing during rush hours is serious. Therefore, increasing the number of shared bikes in parking spots can ease the rebalancing. At the same time, we find that commuting to and from work is not the main factor that constitutes the rebalancing of the free-floating bike-sharing system, though the rebalancing is proportional to travel frequency.

Suggested Citation

  • Wenbin Zhang & Xiaolei Niu & Guangyong Zhang & Lixin Tian, 2022. "Dynamic Rebalancing of the Free-Floating Bike-Sharing System," Sustainability, MDPI, vol. 14(20), pages 1-10, October.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:13521-:d:947295
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    References listed on IDEAS

    as
    1. Legros, Benjamin, 2019. "Dynamic repositioning strategy in a bike-sharing system; how to prioritize and how to rebalance a bike station," European Journal of Operational Research, Elsevier, vol. 272(2), pages 740-753.
    2. Wang, Mingshu & Zhou, Xiaolu, 2017. "Bike-sharing systems and congestion: Evidence from US cities," Journal of Transport Geography, Elsevier, vol. 65(C), pages 147-154.
    3. Li, Weibo & Kamargianni, Maria, 2018. "Providing quantified evidence to policy makers for promoting bike-sharing in heavily air-polluted cities: A mode choice model and policy simulation for Taiyuan-China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 277-291.
    4. Mooney, Stephen J. & Hosford, Kate & Howe, Bill & Yan, An & Winters, Meghan & Bassok, Alon & Hirsch, Jana A., 2019. "Freedom from the station: Spatial equity in access to dockless bike share," Journal of Transport Geography, Elsevier, vol. 74(C), pages 91-96.
    5. Zhang, Yongping & Mi, Zhifu, 2018. "Environmental benefits of bike sharing: A big data-based analysis," Applied Energy, Elsevier, vol. 220(C), pages 296-301.
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