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Diversity of individual mobility patterns and emergence of aggregated scaling laws

Uncovering human mobility patterns is of fundamental importance to the understanding of epidemic spreading, urban transportation and other socioeconomic dynamics embodying spatiality and human travel. According to the direct travel diaries of volunteers, we show the absence of scaling properties in...

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Detalles Bibliográficos
Autores principales: Yan, Xiao-Yong, Han, Xiao-Pu, Wang, Bing-Hong, Zhou, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3776193/
https://www.ncbi.nlm.nih.gov/pubmed/24045416
http://dx.doi.org/10.1038/srep02678
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author Yan, Xiao-Yong
Han, Xiao-Pu
Wang, Bing-Hong
Zhou, Tao
author_facet Yan, Xiao-Yong
Han, Xiao-Pu
Wang, Bing-Hong
Zhou, Tao
author_sort Yan, Xiao-Yong
collection PubMed
description Uncovering human mobility patterns is of fundamental importance to the understanding of epidemic spreading, urban transportation and other socioeconomic dynamics embodying spatiality and human travel. According to the direct travel diaries of volunteers, we show the absence of scaling properties in the displacement distribution at the individual level,while the aggregated displacement distribution follows a power law with an exponential cutoff. Given the constraint on total travelling cost, this aggregated scaling law can be analytically predicted by the mixture nature of human travel under the principle of maximum entropy. A direct corollary of such theory is that the displacement distribution of a single mode of transportation should follow an exponential law, which also gets supportive evidences in known data. We thus conclude that the travelling cost shapes the displacement distribution at the aggregated level.
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spelling pubmed-37761932013-09-18 Diversity of individual mobility patterns and emergence of aggregated scaling laws Yan, Xiao-Yong Han, Xiao-Pu Wang, Bing-Hong Zhou, Tao Sci Rep Article Uncovering human mobility patterns is of fundamental importance to the understanding of epidemic spreading, urban transportation and other socioeconomic dynamics embodying spatiality and human travel. According to the direct travel diaries of volunteers, we show the absence of scaling properties in the displacement distribution at the individual level,while the aggregated displacement distribution follows a power law with an exponential cutoff. Given the constraint on total travelling cost, this aggregated scaling law can be analytically predicted by the mixture nature of human travel under the principle of maximum entropy. A direct corollary of such theory is that the displacement distribution of a single mode of transportation should follow an exponential law, which also gets supportive evidences in known data. We thus conclude that the travelling cost shapes the displacement distribution at the aggregated level. Nature Publishing Group 2013-09-18 /pmc/articles/PMC3776193/ /pubmed/24045416 http://dx.doi.org/10.1038/srep02678 Text en Copyright © 2013, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by/3.0/ This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/
spellingShingle Article
Yan, Xiao-Yong
Han, Xiao-Pu
Wang, Bing-Hong
Zhou, Tao
Diversity of individual mobility patterns and emergence of aggregated scaling laws
title Diversity of individual mobility patterns and emergence of aggregated scaling laws
title_full Diversity of individual mobility patterns and emergence of aggregated scaling laws
title_fullStr Diversity of individual mobility patterns and emergence of aggregated scaling laws
title_full_unstemmed Diversity of individual mobility patterns and emergence of aggregated scaling laws
title_short Diversity of individual mobility patterns and emergence of aggregated scaling laws
title_sort diversity of individual mobility patterns and emergence of aggregated scaling laws
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3776193/
https://www.ncbi.nlm.nih.gov/pubmed/24045416
http://dx.doi.org/10.1038/srep02678
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