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Mobility Pattern of Taxi Passengers at Intra-Urban Scale: Empirical Study of Three Cities

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Listed:
  • Xu Mengqiao

    (Faculty of Management and Economics, Dalian University of Technology, Dalian116024, China)

  • Zhang Ling

    (Faculty of Management and Economics, Dalian University of Technology, Dalian116024, China)

  • Li Wen

    (Faculty of Management and Economics, Dalian University of Technology, Dalian116024, China)

  • Xia Haoxiang

    (Faculty of Management and Economics, Dalian University of Technology, Dalian116024, China)

Abstract

The study of human mobility patterns is of both theoretical and practical values in many aspects. For long-distance travel, a few research endeavors have shown that the displacements of human travels follow a power-law distribution. However, controversies remain regarding the issue of the scaling laws of human mobility in intra-urban areas. In this work, we focus on the mobility pattern of taxi passengers by examining five datasets of three metropolitans. Through statistical analysis, we find that the lognormal distribution with a power-law tail can best approximate both the displacement and the duration time of taxi trips in all the examined cities. The universality of the scaling laws of human mobility is subsequently discussed, in view of the analysis of the data. The consistency of the statistical properties of the selected datasets that cover different cities and study periods suggests that, the identified pattern of taxi-based intra-urban travels seems to be ubiquitous over cities and time periods.

Suggested Citation

  • Xu Mengqiao & Zhang Ling & Li Wen & Xia Haoxiang, 2017. "Mobility Pattern of Taxi Passengers at Intra-Urban Scale: Empirical Study of Three Cities," Journal of Systems Science and Information, De Gruyter, vol. 5(6), pages 537-555, December.
  • Handle: RePEc:bpj:jossai:v:5:y:2017:i:6:p:537-555:n:4
    DOI: 10.21078/JSSI-2017-537-19
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    References listed on IDEAS

    as
    1. Yao, Can-Zhong & Lin, Ji-Nan, 2016. "A study of human mobility behavior dynamics: A perspective of a single vehicle with taxi," Transportation Research Part A: Policy and Practice, Elsevier, vol. 87(C), pages 51-58.
    2. Csáji, Balázs Cs. & Browet, Arnaud & Traag, V.A. & Delvenne, Jean-Charles & Huens, Etienne & Van Dooren, Paul & Smoreda, Zbigniew & Blondel, Vincent D., 2013. "Exploring the mobility of mobile phone users," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1459-1473.
    3. Wang, Wenjun & Pan, Lin & Yuan, Ning & Zhang, Sen & Liu, Dong, 2015. "A comparative analysis of intra-city human mobility by taxi," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 134-147.
    4. Liang, Xiao & Zheng, Xudong & Lv, Weifeng & Zhu, Tongyu & Xu, Ke, 2012. "The scaling of human mobility by taxis is exponential," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(5), pages 2135-2144.
    5. D. Brockmann & L. Hufnagel & T. Geisel, 2006. "The scaling laws of human travel," Nature, Nature, vol. 439(7075), pages 462-465, January.
    6. Liu, Xi & Gong, Li & Gong, Yongxi & Liu, Yu, 2015. "Revealing travel patterns and city structure with taxi trip data," Journal of Transport Geography, Elsevier, vol. 43(C), pages 78-90.
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