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Identification of Metro-Bikeshare Transfer Trip Chains by Matching Docked Bikeshare and Metro Smartcards

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Listed:
  • Xinwei Ma

    (School of Civil and Transportation Engineering, Hebei University of Technology, Tianjin 300401, China)

  • Shuai Zhang

    (School of Civil and Transportation Engineering, Hebei University of Technology, Tianjin 300401, China)

  • Yuchuan Jin

    (School of Architecture and the Built Environment, Royal Institute of Technology (KTH), 114 28 Stockholm, Sweden)

  • Minqing Zhu

    (School of Architecture and Art Design, Hebei University of Technology, Tianjin 300401, China)

  • Yufei Yuan

    (Department of Transport & Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, P.O. Box 5048, 2600 GA Delft, The Netherlands)

Abstract

Metro-bikeshare integration, an important way of improving the efficiency of public transportation, has grown rapidly during the last decades in many countries. However, most previous analysis of metro-bikeshare transfer trips were based on limited sample size and the number of recognized metro-bikeshare trips were not sufficient. The primary objective of this study is to derive a method to recognize metro-bikeshare transfer trips. The two data sources are provided by Nanjing Metro Company and Nanjing Public Bicycle Company over the same period from 9–29 March 2016. The identifying method includes three steps: (1) Matching Card Pairs (2) Filtering Card Pairs and (3) Identifying Card Pairs. The case study indicates that the Support Vector Classification (SVC) performs best with a high prediction accuracy of 95.9% using seamless smartcards. The identifying method is then used to recognize the transfer trips from other types of cards, resulting in 17,022 valid metro-bikeshare transfer trips made by 2948 travelers. Finally, travel patterns extracted from the two groups of identified transfer trips are analyzed comparatively. The method proposed presents new opportunities for analyzing metro-bikeshare transfer trip characteristics.

Suggested Citation

  • Xinwei Ma & Shuai Zhang & Yuchuan Jin & Minqing Zhu & Yufei Yuan, 2021. "Identification of Metro-Bikeshare Transfer Trip Chains by Matching Docked Bikeshare and Metro Smartcards," Energies, MDPI, vol. 15(1), pages 1-19, December.
    • Handle: RePEc:gam:jeners:v:15:y:2021:i:1:p:203-:d:713582
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    References listed on IDEAS

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    1. Martin, Elliot W. & Shaheen, Susan A., 2014. "Evaluating public transit modal shift dynamics in response to bikesharing: a tale of two U.S. cities," Journal of Transport Geography, Elsevier, vol. 41(C), pages 315-324.
    2. Martin, Elliot PhD & Shaheen, Susan PhD, 2014. "Evaluating Public Transit Modal Shift Dynamics In Response to Bikesharing: A Tale of Two U.S. Cities," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6x29n876, Institute of Transportation Studies, UC Berkeley.
    3. Shelat, Sanmay & Huisman, Raymond & van Oort, Niels, 2018. "Analysing the trip and user characteristics of the combined bicycle and transit mode," Research in Transportation Economics, Elsevier, vol. 69(C), pages 68-76.
    4. Tilahun, Nebiyou & Thakuriah, Piyushimita (Vonu) & Li, Moyin & Keita, Yaye, 2016. "Transit use and the work commute: Analyzing the role of last mile issues," Journal of Transport Geography, Elsevier, vol. 54(C), pages 359-368.
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    1. Liu, Yang & Feng, Tao & Shi, Zhuangbin & He, Mingwei, 2022. "Understanding the route choice behaviour of metro-bikeshare users," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 460-475.

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