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Smart card data-centric replication of the multi-modal public transport system in Singapore

Author

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  • Liu, Xiaodong
  • Zhou, Yuan
  • Rau, Andreas

Abstract

This paper proposes an innovative method of replicating the multi-modal public transport system in Singapore with high precision using smart card database. It replicates the operation of public transport system with known exogenous passenger demand and provides many operational details, including passenger inter-modal trip chains, operational timetable, and detailed transfer behaviour. The paper elaborates on the methodology of the replication including data cleaning, filtering, processing and converting the collected data to meaningful information such as bus journey trajectories and metro system timetable. Thereafter, actualised passenger trip chains are directly assigned to the replicated public transport supply. The resulting replication covers almost 96% of trips made in public transport in Singapore. It provides solid quantitative information on several aspects to support decision making, including precise temporal and spatial travel demand analysis, transfer pattern analysis, traffic condition investigation and bus utilisation analysis.

Suggested Citation

  • Liu, Xiaodong & Zhou, Yuan & Rau, Andreas, 2019. "Smart card data-centric replication of the multi-modal public transport system in Singapore," Journal of Transport Geography, Elsevier, vol. 76(C), pages 254-264.
  • Handle: RePEc:eee:jotrge:v:76:y:2019:i:c:p:254-264
    DOI: 10.1016/j.jtrangeo.2018.02.004
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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. Vrtic, M. & Fröhlich, P. & Schüssler, N. & Axhausen, K.W. & Lohse, D. & Schiller, C. & Teichert, H., 2007. "Two-dimensionally constrained disaggregate trip generation, distribution and mode choice model: Theory and application for a Swiss national model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(9), pages 857-873, November.
    3. Bueno, Paola Carolina & Gomez, Juan & Peters, Jonathan R. & Vassallo, Jose Manuel, 2017. "Understanding the effects of transit benefits on employees’ travel behavior: Evidence from the New York-New Jersey region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 99(C), pages 1-13.
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    Cited by:

    1. Arbex, Renato & Cunha, Claudio B., 2020. "Estimating the influence of crowding and travel time variability on accessibility to jobs in a large public transport network using smart card big data," Journal of Transport Geography, Elsevier, vol. 85(C).

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