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Journey-based characterization of multi-modal public transportation networks

Author

Listed:
  • Cecilia Viggiano

    (Massachusetts Institute of Technology)

  • Haris N. Koutsopoulos

    (Northeastern University, 403 Snell Engineering Center)

  • Nigel H. M. Wilson

    (Massachusetts Institute of Technology)

  • John Attanucci

    (Massachusetts Institute of Technology)

Abstract

Planners must understand how public transportation systems are used in order to make strategic decisions. Smart card transaction data provides vast, detailed records of network usage. Combined with other automatically collected data sources, established inference methodologies can convert smart card transactions into complete linked journeys made by individuals within the public transport network. However, for large, multi-modal public transport networks it can be challenging to summarize the journey records meaningfully. This paper develops a method for categorizing origin–destination (OD) pairs by public transport mode or combination of used modes. By aggregating across OD pairs, this categorization scheme summarizes the multi-modal aspects of public transport network usage. The methodology can also be applied to subsets of data filtered by time of day or geography. The categorization results can inform performance analysis of OD pairs, allowing planners to make comparisons between pairs served by different combinations of modes. London Oyster card data is analyzed to illustrate how the OD pair categorization can characterize a network, allowing planners to quickly assess the roles of different modes, and perform OD pair analysis in a multi-modal public transport network.

Suggested Citation

  • Cecilia Viggiano & Haris N. Koutsopoulos & Nigel H. M. Wilson & John Attanucci, 2017. "Journey-based characterization of multi-modal public transportation networks," Public Transport, Springer, vol. 9(1), pages 437-461, July.
    • Handle: RePEc:spr:pubtra:v:9:y:2017:i:1:d:10.1007_s12469-016-0145-8
    DOI: 10.1007/s12469-016-0145-8
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    References listed on IDEAS

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    1. Bagchi, M. & White, P.R., 2005. "The potential of public transport smart card data," Transport Policy, Elsevier, vol. 12(5), pages 464-474, September.
    2. Morency, Catherine & Trépanier, Martin & Agard, Bruno, 2007. "Measuring transit use variability with smart-card data," Transport Policy, Elsevier, vol. 14(3), pages 193-203, May.
    3. Sybil Derrible & Christopher Kennedy, 2010. "Characterizing metro networks: state, form, and structure," Transportation, Springer, vol. 37(2), pages 275-297, March.
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    Cited by:

    1. Filip Covic & Stefan Voß, 2019. "Interoperable smart card data management in public mass transit," Public Transport, Springer, vol. 11(3), pages 523-548, October.
    2. Li He & Martin Trépanier & Bruno Agard, 2021. "Space–time classification of public transit smart card users’ activity locations from smart card data," Public Transport, Springer, vol. 13(3), pages 579-595, October.
    3. Naima Islam & Md Abu Sufian Talukder & Alex Hainen & Travis Atkison, 2020. "Characterizing co-modality in urban transit systems from a passengers’ perspective," Public Transport, Springer, vol. 12(2), pages 405-430, June.

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