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Analysis of Network Structure of Urban Bike-Sharing System: A Case Study Based on Real-Time Data of a Public Bicycle System

Author

Listed:
  • Yi Yao

    (School of Mathematical Sciences, Nanjing Normal University, Nanjing 210023, China)

  • Yifang Zhang

    (School of Mathematical Sciences, Nanjing Normal University, Nanjing 210023, China)

  • Lixin Tian

    (School of Mathematical Sciences, Nanjing Normal University, Nanjing 210023, China)

  • Nianxing Zhou

    (School of Geography, Nanjing Normal University, Nanjing 210023, China)

  • Zhilin Li

    (Department of Mathematics, North Carolina State University, NC 27695, USA)

  • Minggang Wang

    (School of Mathematical Sciences, Nanjing Normal University, Nanjing 210023, China
    Department of Mathematics, Nanjing Normal University Taizhou College, Taizhou 225300, China)

Abstract

To better understand the characteristics of a bike-sharing system, we applied complex network methods to analyze the relationship between stations within the bike-sharing system. Firstly, using Gephi software, we constructed the public bicycle networks of different urban areas based on the real-time data of the Nanjing public bicycle system. Secondly, we analyzed and compared degree, strength, radiation distance, and community structure of the networks to understand the internal relations of the public bicycle system. The results showed that there were many stations with low usage of public bicycles. Furthermore, there was a geographical division between high-demand and low-demand areas for public bicycles. The usage of public bicycles at a station was not only related to land use but also related to the usage of bicycles at stations nearby. Moreover, the average service coverage of the public bicycle system was consistent with the original intention of “the first and last mile”, and public bicycles could meet different travel needs.

Suggested Citation

  • Yi Yao & Yifang Zhang & Lixin Tian & Nianxing Zhou & Zhilin Li & Minggang Wang, 2019. "Analysis of Network Structure of Urban Bike-Sharing System: A Case Study Based on Real-Time Data of a Public Bicycle System," Sustainability, MDPI, vol. 11(19), pages 1-17, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5425-:d:272379
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    3. Sara Poveda-Reyes & Ashwani Kumar Malviya & Elena García-Jiménez & Gemma Dolores Molero & Maria Chiara Leva & Francisco Enrique Santarremigia, 2021. "Application of Mathematical and Computational Methods to Identify Women’s Priorities in Transport," Sustainability, MDPI, vol. 13(5), pages 1-43, March.
    4. Radzimski, Adam & Dzięcielski, Michał, 2021. "Exploring the relationship between bike-sharing and public transport in Poznań, Poland," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 189-202.
    5. De Zhao & Ghim Ping Ong & Wei Wang & Wei Zhou, 2021. "Estimating Public Bicycle Trip Characteristics with Consideration of Built Environment Data," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
    6. Xu, Xiaohan & Huang, Ailing & Shalaby, Amer & Feng, Qian & Chen, Mingyang & Qi, Geqi, 2024. "Exploring cascading failure processes of interdependent multi-modal public transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).
    7. Jacek Oskarbski & Krystian Birr & Karol Żarski, 2021. "Bicycle Traffic Model for Sustainable Urban Mobility Planning," Energies, MDPI, vol. 14(18), pages 1-36, September.

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