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Human mobility in bike-sharing systems: Structure of local and non-local dynamics

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  • D Loaiza-Monsalve
  • A P Riascos

Abstract

The understanding of human mobility patterns in different transportation modes is an interdisciplinary research field with a direct impact in aspects as varied as urban planning, traffic optimization, sustainability, the reduction of operating costs as well as the mitigation of pollution in urban areas. In this paper, we study the global activity of users in bike-sharing systems operating in the cities of Chicago and New York. For this transportation mode, we explore the temporal and spatial characteristics of the mobility of cyclists. In particular, through the analysis of origin-destination matrices, we characterize the spatial structure of the displacements of users. We apply a mobility model for the global activity of the system that classifies the displacements between stations in local and non-local transitions. In local transitions, cyclists move in a region around each station whereas, in the non-local case, bike users travel with long-range displacements in a similar way to Lévy flights. We reproduce the spatial dynamics by using Monte Carlo simulations. The obtained results are similar to the observed in real data and reveal that the model implemented captures important characteristics of the global spatial dynamics in the systems analyzed.

Suggested Citation

  • D Loaiza-Monsalve & A P Riascos, 2019. "Human mobility in bike-sharing systems: Structure of local and non-local dynamics," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-17, March.
    • Handle: RePEc:plo:pone00:0213106
    DOI: 10.1371/journal.pone.0213106
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    References listed on IDEAS

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    1. Carson Qing & Wei Hao, 2018. "A Methodology for Measuring and Monitoring Congested Corridors: Applications in Manhattan Using Taxi GPS Data," Journal of Urban Technology, Taylor & Francis Journals, vol. 25(4), pages 59-75, October.
    2. Chengbin Peng & Xiaogang Jin & Ka-Chun Wong & Meixia Shi & Pietro Liò, 2012. "Collective Human Mobility Pattern from Taxi Trips in Urban Area," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-8, April.
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    Cited by:

    1. Zhan Gao & Sheng Wei & Lei Wang & Sijia Fan, 2020. "Exploring the Spatial-Temporal Characteristics of Traditional Public Bicycle Use in Yancheng, China: A Perspective of Time Series Cluster of Stations," Sustainability, MDPI, vol. 12(16), pages 1-17, August.

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