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Investigation of Changes in Passenger Behavior Using Longitudinal Smart Card Data

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Abstract

To better understand long-term patterns of human mobility, this study examines changes in travel behavior at the individual level based on yearly activity profiles using 3 years of longitudinal smart card data collected in Shizuoka, Japan. We first characterize spatiotemporal patterns of railway usage by k-means clustering, and then investigate variation in cluster membership with time. For among passengers who remained active, regular commuters had similar travel patterns over the study period, whereas infrequent travelers significantly increased their use of the railway system. The evolution of cluster assignment is analyzed and discussed.

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Acknowledgments

The authors would like to thank to Shizuoka Railway Co., Ltd. for providing the LuLuCa smart card dataset used in this research.

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Authors and Affiliations

  1. Department of Civil Engineering, Gifu University, 1−1 Yanagido, Gifu, 501-1193, Japan

    Rattanaporn Kaewkluengklom & Fumitaka Kurauchi

  2. Shizuoka Railway Co., Ltd., 1-1-1 Takajo, Shizuoka, 420-0839, Japan

    Takenori Iwamoto

Authors
  1. Rattanaporn Kaewkluengklom
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  2. Fumitaka Kurauchi
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  3. Takenori Iwamoto
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Correspondence to Rattanaporn Kaewkluengklom.

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Kaewkluengklom, R., Kurauchi, F. & Iwamoto, T. Investigation of Changes in Passenger Behavior Using Longitudinal Smart Card Data. Int. J. ITS Res. 19, 155–166 (2021). https://doi.org/10.1007/s13177-020-00232-3

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  • DOI: https://doi.org/10.1007/s13177-020-00232-3

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