Explaining the power-law distribution of human mobility through transportation modality decomposition

Scientific Reports
Kai ZhaoSasu Tarkoma

Abstract

Human mobility has been empirically observed to exhibit Lévy flight characteristics and behaviour with power-law distributed jump size. The fundamental mechanisms behind this behaviour has not yet been fully explained. In this paper, we propose to explain the Lévy walk behaviour observed in human mobility patterns by decomposing them into different classes according to the different transportation modes, such as Walk/Run, Bike, Train/Subway or Car/Taxi/Bus. Our analysis is based on two real-life GPS datasets containing approximately 10 and 20 million GPS samples with transportation mode information. We show that human mobility can be modelled as a mixture of different transportation modes, and that these single movement patterns can be approximated by a lognormal distribution rather than a power-law distribution. Then, we demonstrate that the mixture of the decomposed lognormal flight distributions associated with each modality is a power-law distribution, providing an explanation to the emergence of Lévy Walk patterns that characterize human mobility patterns.

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Citations

Sep 23, 2016·PloS One·Philip S ChodrowMarta C González
Jul 15, 2015·PloS One·Raja JurdakDavid Newth
Feb 16, 2017·PloS One·Laura AlessandrettiAndrea Baronchelli
Oct 13, 2017·PloS One·A P Riascos, José L Mateos
Aug 31, 2016·Nature Communications·Riccardo GallottiMarc Barthelemy
Apr 17, 2019·PloS One·Jinzhou CaoFeilong Wang
Feb 14, 2018·Journal of the Royal Society, Interface·Riccardo GallottiMarc Barthelemy
Jul 26, 2017·Scientific Reports·Wei Geng, Guang Yang
Apr 30, 2019·Royal Society Open Science·Liam D TurnerDon Towsley
Feb 18, 2017·Physical Review. E·Deepika Janakiraman
Dec 10, 2020·Scientific Reports·Yohei ShidaMisako Takayasu
Feb 12, 2021·PLoS Computational Biology·Constanze Ciavarella, Neil M Ferguson

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