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Examining and optimizing the BCycle bike-sharing system – A pilot study in Colorado, US

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  • Hu, Yujie
  • Zhang, Yongping
  • Lamb, David
  • Zhang, Mingming
  • Jia, Peng

Abstract

Many cities around the world have integrated bike-sharing programs into their public transit systems to promise sustainable, affordable transportation and reduce environmental pollution in urban areas. Investigating the usage patterns of shared bikes is of key importance to understand cyclist’s behaviors and subsequently optimize bike-sharing programs. Based on the historical trip records of bike users and station empty/full status data, this paper evaluated and optimized the bike-sharing program BCycle in the city of Boulder, Colorado, the United States, using a combination of different methods including the Potential Path Area (PPA) and the Capacitated Maximal Covering Location Problem (CMCLP). Results showed significantly different usage patterns between membership groups, revealed diverse imbalance patterns of bike supply and demand across stations in the city and provided three system upgrading strategies about maximizing the service coverage. This case study is committed to future energy conservation and sustainable energy systems nationwide and ultimately worldwide, by holding immerse potential to adapt the resulting optimization strategies to the cities with a similar urban context across the United States, as well as more emerging bike-sharing programs in other countries, such as China.

Suggested Citation

  • Hu, Yujie & Zhang, Yongping & Lamb, David & Zhang, Mingming & Jia, Peng, 2019. "Examining and optimizing the BCycle bike-sharing system – A pilot study in Colorado, US," Applied Energy, Elsevier, vol. 247(C), pages 1-12.
  • Handle: RePEc:eee:appene:v:247:y:2019:i:c:p:1-12
    DOI: 10.1016/j.apenergy.2019.04.007
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    Cited by:

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    2. Zhang, Haoran & Chen, Jinyu & Li, Wenjing & Song, Xuan & Shibasaki, Ryosuke, 2020. "Mobile phone GPS data in urban ride-sharing: An assessment method for emission reduction potential," Applied Energy, Elsevier, vol. 269(C).
    3. Cheng, Xiu & Long, Ruyin & Chen, Hong & Yang, Jiahui, 2019. "Does social interaction have an impact on residents’ sustainable lifestyle decisions? A multi-agent stimulation based on regret and game theory," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    4. Rodrigo Mora & Pablo Moran, 2020. "Public Bike Sharing Programs Under the Prism of Urban Planning Officials: The Case of Santiago de Chile," Sustainability, MDPI, vol. 12(14), pages 1-20, July.
    5. 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).
    6. Bergantino, Angela Stefania & Intini, Mario & Tangari, Luca, 2021. "Influencing factors for potential bike-sharing users: an empirical analysis during the COVID-19 pandemic," Research in Transportation Economics, Elsevier, vol. 86(C).
    7. Schimohr, Katja & Scheiner, Joachim, 2021. "Spatial and temporal analysis of bike-sharing use in Cologne taking into account a public transit disruption," Journal of Transport Geography, Elsevier, vol. 92(C).
    8. Hu, Yujie & Wang, Changzhen & Li, Ruiyang & Wang, Fahui, 2020. "Estimating a large drive time matrix between ZIP codes in the United States: A differential sampling approach," Journal of Transport Geography, Elsevier, vol. 86(C).

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