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Understanding the Heterogeneity of Human Mobility Patterns: User Characteristics and Modal Preferences

Author

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  • Laiyun Wu

    (Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, NY 14260, USA)

  • Samiul Hasan

    (College of Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USA)

  • Younshik Chung

    (Department of Urban Planning and Engineering, Yeungnam University, Gyeungsan 38541, Korea)

  • Jee Eun Kang

    (Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, NY 14260, USA)

Abstract

Characterizing individual mobility is critical to understand urban dynamics and to develop high-resolution mobility models. Previously, large-scale trajectory datasets have been used to characterize universal mobility patterns. However, due to the limitations of the underlying datasets, these studies could not investigate how mobility patterns differ over user characteristics among demographic groups. In this study, we analyzed a large-scale Automatic Fare Collection (AFC) dataset of the transit system of Seoul, South Korea and investigated how mobility patterns vary over user characteristics and modal preferences. We identified users’ commuting locations and estimated the statistical distributions required to characterize their spatio-temporal mobility patterns. Our findings show the heterogeneity of mobility patterns across demographic user groups. This result will significantly impact future mobility models based on trajectory datasets.

Suggested Citation

  • Laiyun Wu & Samiul Hasan & Younshik Chung & Jee Eun Kang, 2021. "Understanding the Heterogeneity of Human Mobility Patterns: User Characteristics and Modal Preferences," Sustainability, MDPI, vol. 13(24), pages 1-18, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:24:p:13921-:d:704066
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    References listed on IDEAS

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    1. Yu Liu & Zhengwei Sui & Chaogui Kang & Yong Gao, 2014. "Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-11, January.
    2. Marta C. González & César A. Hidalgo & Albert-László Barabási, 2009. "Understanding individual human mobility patterns," Nature, Nature, vol. 458(7235), pages 238-238, March.
    3. D. Brockmann & L. Hufnagel & T. Geisel, 2006. "The scaling laws of human travel," Nature, Nature, vol. 439(7075), pages 462-465, January.
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