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GPS data in urban bicycle-sharing: Dynamic electric fence planning with assessment of resource-saving and potential energy consumption increasement

Author

Listed:
  • Yu, Qing
  • Xie, Yingkun
  • Li, Weifeng
  • Zhang, Haoran
  • Liu, Xiaolei
  • Shang, Wen-Long
  • Chen, Jinyu
  • Yang, Dongyuan
  • Yan, Jinyue

Abstract

As a newly-emerging option of shared transportation, Internet-enabled dockless bicycle sharing is well accepted by the public. The implementation of electric fences has great potential to tackle the problem of random parking in bicycle sharing services. However, the deployment of electric fences would have a negative impact on the convenience of bicycle sharing services, which might lead to an increase in energy consumption among customers who switch their methods of transportation. This paper proposes a dynamic electric fence planning method with an assessment of resource-saving and potential energy consumption increasement. An agent-based model is proposed to simulate the trips and evaluated the performance of static and dynamic electric fences. The results show that dynamic electric fences require significantly shorter walking distances than static electric fences. The implementation of electric fences in the city center can significantly avoid random parking and improve the parking tidiness of bicycles. The implementation of dynamic and static electric fences can averagely save 25.31% and 27.76% bicycle resources. By estimating travel mode shifting, dynamic electric fence can reduce energy consumption by 5.79% per day compared to the static electric fence situation.

Suggested Citation

  • Yu, Qing & Xie, Yingkun & Li, Weifeng & Zhang, Haoran & Liu, Xiaolei & Shang, Wen-Long & Chen, Jinyu & Yang, Dongyuan & Yan, Jinyue, 2022. "GPS data in urban bicycle-sharing: Dynamic electric fence planning with assessment of resource-saving and potential energy consumption increasement," Applied Energy, Elsevier, vol. 322(C).
    • Handle: RePEc:eee:appene:v:322:y:2022:i:c:s0306261922008509
    DOI: 10.1016/j.apenergy.2022.119533
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    References listed on IDEAS

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    1. Médard de Chardon, Cyrille & Caruso, Geoffrey & Thomas, Isabelle, 2016. "Bike-share rebalancing strategies, patterns, and purpose," Journal of Transport Geography, Elsevier, vol. 55(C), pages 22-39.
    2. Böcker, Lars & Anderson, Ellinor & Uteng, Tanu Priya & Throndsen, Torstein, 2020. "Bike sharing use in conjunction to public transport: Exploring spatiotemporal, age and gender dimensions in Oslo, Norway," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 389-401.
    3. Qiang Yan & Kun Gao & Lijun Sun & Minhua Shao, 2020. "Spatio-Temporal Usage Patterns of Dockless Bike-Sharing Service Linking to a Metro Station: A Case Study in Shanghai, China," Sustainability, MDPI, vol. 12(3), pages 1-14, January.
    4. Zhang, Dong & Yu, Chuhang & Desai, Jitamitra & Lau, H.Y.K. & Srivathsan, Sandeep, 2017. "A time-space network flow approach to dynamic repositioning in bicycle sharing systems," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 188-207.
    5. Zhifu Mi & D’Maris Coffman, 2019. "The sharing economy promotes sustainable societies," Nature Communications, Nature, vol. 10(1), pages 1-3, December.
    6. Kim, Kyoungok, 2018. "Investigation on the effects of weather and calendar events on bike-sharing according to the trip patterns of bike rentals of stations," Journal of Transport Geography, Elsevier, vol. 66(C), pages 309-320.
    7. Zhang, Yongping & Lin, Diao & Liu, Xiaoyue Cathy, 2019. "Biking islands in cities: An analysis combining bike trajectory and percolation theory," Journal of Transport Geography, Elsevier, vol. 80(C).
    8. Yu, Qing & Li, Weifeng & Zhang, Haoran & Chen, Jinyu, 2022. "GPS data in taxi-sharing system: Analysis of potential demand and assessment of fuel consumption based on routing probability model," Applied Energy, Elsevier, vol. 314(C).
    9. Shang, Wen-Long & Chen, Jinyu & Bi, Huibo & Sui, Yi & Chen, Yanyan & Yu, Haitao, 2021. "Impacts of COVID-19 pandemic on user behaviors and environmental benefits of bike sharing: A big-data analysis," Applied Energy, Elsevier, vol. 285(C).
    10. Schuijbroek, J. & Hampshire, R.C. & van Hoeve, W.-J., 2017. "Inventory rebalancing and vehicle routing in bike sharing systems," European Journal of Operational Research, Elsevier, vol. 257(3), pages 992-1004.
    11. Zhang, Haoran & Song, Xuan & Long, Yin & Xia, Tianqi & Fang, Kai & Zheng, Jianqin & Huang, Dou & Shibasaki, Ryosuke & Liang, Yongtu, 2019. "Mobile phone GPS data in urban bicycle-sharing: Layout optimization and emissions reduction analysis," Applied Energy, Elsevier, vol. 242(C), pages 138-147.
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