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Collective Human Mobility Pattern from Taxi Trips in Urban Area

We analyze the passengers' traffic pattern for 1.58 million taxi trips of Shanghai, China. By employing the non-negative matrix factorization and optimization methods, we find that, people travel on workdays mainly for three purposes: commuting between home and workplace, traveling from workpla...

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Autores principales: Peng, Chengbin, Jin, Xiaogang, Wong, Ka-Chun, Shi, Meixia, Liò, Pietro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3329492/
https://www.ncbi.nlm.nih.gov/pubmed/22529917
http://dx.doi.org/10.1371/journal.pone.0034487
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author Peng, Chengbin
Jin, Xiaogang
Wong, Ka-Chun
Shi, Meixia
Liò, Pietro
author_facet Peng, Chengbin
Jin, Xiaogang
Wong, Ka-Chun
Shi, Meixia
Liò, Pietro
author_sort Peng, Chengbin
collection PubMed
description We analyze the passengers' traffic pattern for 1.58 million taxi trips of Shanghai, China. By employing the non-negative matrix factorization and optimization methods, we find that, people travel on workdays mainly for three purposes: commuting between home and workplace, traveling from workplace to workplace, and others such as leisure activities. Therefore, traffic flow in one area or between any pair of locations can be approximated by a linear combination of three basis flows, corresponding to the three purposes respectively. We name the coefficients in the linear combination as traffic powers, each of which indicates the strength of each basis flow. The traffic powers on different days are typically different even for the same location, due to the uncertainty of the human motion. Therefore, we provide a probability distribution function for the relative deviation of the traffic power. This distribution function is in terms of a series of functions for normalized binomial distributions. It can be well explained by statistical theories and is verified by empirical data. These findings are applicable in predicting the road traffic, tracing the traffic pattern and diagnosing the traffic related abnormal events. These results can also be used to infer land uses of urban area quite parsimoniously.
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spelling pubmed-33294922012-04-23 Collective Human Mobility Pattern from Taxi Trips in Urban Area Peng, Chengbin Jin, Xiaogang Wong, Ka-Chun Shi, Meixia Liò, Pietro PLoS One Research Article We analyze the passengers' traffic pattern for 1.58 million taxi trips of Shanghai, China. By employing the non-negative matrix factorization and optimization methods, we find that, people travel on workdays mainly for three purposes: commuting between home and workplace, traveling from workplace to workplace, and others such as leisure activities. Therefore, traffic flow in one area or between any pair of locations can be approximated by a linear combination of three basis flows, corresponding to the three purposes respectively. We name the coefficients in the linear combination as traffic powers, each of which indicates the strength of each basis flow. The traffic powers on different days are typically different even for the same location, due to the uncertainty of the human motion. Therefore, we provide a probability distribution function for the relative deviation of the traffic power. This distribution function is in terms of a series of functions for normalized binomial distributions. It can be well explained by statistical theories and is verified by empirical data. These findings are applicable in predicting the road traffic, tracing the traffic pattern and diagnosing the traffic related abnormal events. These results can also be used to infer land uses of urban area quite parsimoniously. Public Library of Science 2012-04-18 /pmc/articles/PMC3329492/ /pubmed/22529917 http://dx.doi.org/10.1371/journal.pone.0034487 Text en Peng et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Peng, Chengbin
Jin, Xiaogang
Wong, Ka-Chun
Shi, Meixia
Liò, Pietro
Collective Human Mobility Pattern from Taxi Trips in Urban Area
title Collective Human Mobility Pattern from Taxi Trips in Urban Area
title_full Collective Human Mobility Pattern from Taxi Trips in Urban Area
title_fullStr Collective Human Mobility Pattern from Taxi Trips in Urban Area
title_full_unstemmed Collective Human Mobility Pattern from Taxi Trips in Urban Area
title_short Collective Human Mobility Pattern from Taxi Trips in Urban Area
title_sort collective human mobility pattern from taxi trips in urban area
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3329492/
https://www.ncbi.nlm.nih.gov/pubmed/22529917
http://dx.doi.org/10.1371/journal.pone.0034487
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