Collective human mobility pattern from taxi trips in urban area

Handle URI:
http://hdl.handle.net/10754/325304
Title:
Collective human mobility pattern from taxi trips in urban area
Authors:
Peng, Chengbin ( 0000-0002-7445-2638 ) ; Jin, Xiaogang; Wong, Ka-Chun; Shi, Meixia; Liò, Pietro
Abstract:
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. 2012 Peng et al.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Peng C, Jin X, Wong K-C, Shi M, Liò P (2012) Collective Human Mobility Pattern from Taxi Trips in Urban Area. PLoS ONE 7: e34487. doi:10.1371/journal.pone.0034487.
Publisher:
Public Library of Science (PLoS)
Journal:
PLoS ONE
Issue Date:
18-Apr-2012
DOI:
10.1371/journal.pone.0034487
PubMed ID:
22529917
PubMed Central ID:
PMC3329492
Type:
Article
ISSN:
19326203
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorPeng, Chengbinen
dc.contributor.authorJin, Xiaogangen
dc.contributor.authorWong, Ka-Chunen
dc.contributor.authorShi, Meixiaen
dc.contributor.authorLiò, Pietroen
dc.date.accessioned2014-08-27T09:46:00Z-
dc.date.available2014-08-27T09:46:00Z-
dc.date.issued2012-04-18en
dc.identifier.citationPeng C, Jin X, Wong K-C, Shi M, Liò P (2012) Collective Human Mobility Pattern from Taxi Trips in Urban Area. PLoS ONE 7: e34487. doi:10.1371/journal.pone.0034487.en
dc.identifier.issn19326203en
dc.identifier.pmid22529917en
dc.identifier.doi10.1371/journal.pone.0034487en
dc.identifier.urihttp://hdl.handle.net/10754/325304en
dc.description.abstractWe 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. 2012 Peng et al.en
dc.language.isoenen
dc.publisherPublic Library of Science (PLoS)en
dc.rightsPeng et al. 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 credited.en
dc.rightsArchived with thanks to PLoS ONEen
dc.subjectChinaen
dc.subjecthomeen
dc.subjectland useen
dc.subjectleisureen
dc.subjectmotor vehicleen
dc.subjectpredictionen
dc.subjectprobabilityen
dc.subjectstatistical analysisen
dc.subjectstatistical distributionen
dc.subjecttrafficen
dc.subjecttravelen
dc.subjecturban areaen
dc.subjectworkplaceen
dc.subjectAlgorithmsen
dc.subjectChinaen
dc.subjectModels, Statisticalen
dc.subjectTransportationen
dc.subjectUrban Populationen
dc.titleCollective human mobility pattern from taxi trips in urban areaen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalPLoS ONEen
dc.identifier.pmcidPMC3329492en
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionInstitute of Artificial Intelligence, College of Computer Science, Zhejiang University, Hangzhou, Chinaen
dc.contributor.institutionCollege of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Chinaen
dc.contributor.institutionComputer Laboratory, Cambridge University, Cambridge, United Kingdomen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorPeng, Chengbinen
kaust.authorWong, Ka Chunen

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