Literature DB >> 19792106

Characterizing the human mobility pattern in a large street network.

Bin Jiang1, Junjun Yin, Sijian Zhao.   

Abstract

Previous studies demonstrated empirically that human mobility exhibits Lévy flight behavior. However, our knowledge of the mechanisms governing this Lévy flight behavior remains limited. Here we analyze over 72,000 people's moving trajectories, obtained from 50 taxicabs during a six-month period in a large street network, and illustrate that the human mobility pattern, or the Lévy flight behavior, is mainly attributed to the underlying street network. In other words, the goal-directed nature of human movement has little effect on the overall traffic distribution. We further simulate the mobility of a large number of random walkers and find that (1) the simulated random walkers can reproduce the same human mobility pattern, and (2) the simulated mobility rate of the random walkers correlates pretty well (an R square up to 0.87) with the observed human mobility rate.

Entities:  

Year:  2009        PMID: 19792106     DOI: 10.1103/PhysRevE.80.021136

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  22 in total

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6.  Geographically Modified PageRank Algorithms: Identifying the Spatial Concentration of Human Movement in a Geospatial Network.

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7.  A Simulation Model for Intra-Urban Movements.

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Journal:  PLoS One       Date:  2015-07-10       Impact factor: 3.240

8.  Correlations and scaling laws in human mobility.

Authors:  Xiang-Wen Wang; Xiao-Pu Han; Bing-Hong Wang
Journal:  PLoS One       Date:  2014-01-13       Impact factor: 3.240

9.  Adaptive Lévy processes and area-restricted search in human foraging.

Authors:  Thomas T Hills; Christopher Kalff; Jan M Wiener
Journal:  PLoS One       Date:  2013-04-05       Impact factor: 3.240

10.  Diversity of individual mobility patterns and emergence of aggregated scaling laws.

Authors:  Xiao-Yong Yan; Xiao-Pu Han; Bing-Hong Wang; Tao Zhou
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

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