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Journey-based characterization of multi-modal public transportation networks

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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.

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Acknowledgements

Many thanks to Transport for London for the support, guidance, and oversight of this research.

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Authors and Affiliations

  1. Massachusetts Institute of Technology, 77 Massachussetts Avenue, Bldg 1-235, Cambridge, MA, 02139, USA

    Cecilia Viggiano, Nigel H. M. Wilson & John Attanucci

  2. Northeastern University, 403 Snell Engineering Center, 360 Huntington Avenue, Boston, MA, 02115, USA

    Haris N. Koutsopoulos

Authors
  1. Cecilia Viggiano
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  2. Haris N. Koutsopoulos
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  3. Nigel H. M. Wilson
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  4. John Attanucci
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Correspondence to Cecilia Viggiano.

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Viggiano, C., Koutsopoulos, H.N., Wilson, N.H.M. et al. Journey-based characterization of multi-modal public transportation networks. Public Transp 9, 437–461 (2017). https://doi.org/10.1007/s12469-016-0145-8

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  • DOI: https://doi.org/10.1007/s12469-016-0145-8

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