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An extended exploration and preferential return model for human mobility simulation at individual and collective levels

Jianying Wang, Lei Dong, Ximeng Cheng, Weijun Yang and Yu Liu

Physica A: Statistical Mechanics and its Applications, 2019, vol. 534, issue C

Abstract: Human mobility models have prevalent applications in traffic management, urban planning, and disease prevention. Modeling human mobility combining both the statistical physical mechanics and geographical constrains is not fully investigated. In this research, we extend the exploration and preferential return (EPR) model by considering both spatial heterogeneity and distance decay. The extended model takes rank distance in the distance decay function, and is validated in four cities based on the population distribution and the trajectory data. Our model not only reproduces the statistics of human mobility at both the individual and collective levels with high accuracy, but also has a robust prediction at both high and low resolutions. The study demonstrates the potential of applications of the human mobility models aggregating the collective and individual levels factors, and sheds light on the trade-off between ‘simple’ mobility rules and ‘complex’ geographical environments.

Keywords: Human mobility; Geographical constrains; Spatial heterogeneity; Exploration and preferential return model (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:534:y:2019:i:c:s037843711931129x

DOI: 10.1016/j.physa.2019.121921

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Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

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