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  • 1.
    Jia, Tao
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Urban and regional planning/GIS-institute. Division of Geoinformatics, Royal Institute of Technology (KTH), Stockholm, Sweden .
    Jiang, Bin
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Urban and regional planning/GIS-institute.
    Carling, Kenneth
    School of Technology and Business Studies, Dalarna University, Borlänge, Sweden .
    Bolin, Magnus
    School of Technology and Business Studies, Dalarna University, Borlänge, Sweden .
    Ban, Yifang
    Division of Geoinformatics, Royal Institute of Technology (KTH), Stockholm, Sweden.
    An empirical study on human mobility and its agent-based modeling2012In: Journal of Statistical Mechanics: Theory and Experiment, ISSN 1742-5468, E-ISSN 1742-5468, no 11, p. P11024-Article in journal (Refereed)
    Abstract [en]

    This paper aims to analyze the GPS traces of 258 volunteers in order to obtain a better understanding of both the human mobility patterns and the mechanism. We report the regular and scaling properties of human mobility for several aspects, and importantly we identify its Levy flight characteristic, which is consistent with those from previous studies. We further assume two factors that may govern the Levy flight property: (1) the scaling and hierarchical properties of the purpose clusters which serve as the underlying spatial structure, and (2) the individual preferential behaviors. To verify the assumptions, we implement an agent-based model with the two factors, and the simulated results do indeed capture the same Levy flight pattern as is observed. In order to enable the model to reproduce more mobility patterns, we add to the model a third factor: the jumping factor, which is the probability that one person may cancel their regular mobility schedule and explore a random place. With this factor, our model can cover a relatively wide range of human mobility patterns with scaling exponent values from 1.55 to 2.05.

  • 2. Jiang, Bin
    et al.
    Zhao, Sijian
    Yin, Junjun
    Self-organized natural roads for predicting traffic flow: a sensitivity study2008In: Journal of Statistical Mechanics: Theory and Experiment, ISSN 1742-5468, E-ISSN 1742-5468, no July, article id P07008Article in journal (Refereed)
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