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Identifying human mobility patterns using smart card data
KTH, Skolan för arkitektur och samhällsbyggnad (ABE), Byggvetenskap, Transportplanering. Delft Univ Technol, Fac Civil Engn & Geosci, Dept Transport & Planning, Delft, Netherlands.;Delft Univ Technol, Fac Civil Engn & Geosci, Dept Transport & Planning, Stevinweg 1, NL-2628 CN Delft, Netherlands..ORCID-id: 0000-0002-4506-0459
2023 (Engelska)Ingår i: Transport reviews, ISSN 0144-1647, E-ISSN 1464-5327, artikel-id 2251688Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Human mobility is subject to collective dynamics that are the outcome of numerous individual choices. Smart card data which originated as a means of facilitating automated fare collection has emerged as an invaluable source for analysing mobility patterns. A variety of clustering and segmentation techniques has been adopted and adapted for applications ranging from market segmentation to the analysis of urban activity locations. In this paper we provide a systematic review of the state-of-the-art on clustering public transport users based on their temporal or spatial-temporal characteristics as well as studies that use the latter to characterise individual stations, lines or urban areas. Furthermore, a critical review of the literature reveals an important distinction between studies focusing on the intra-personal variability of travel patterns versus those concerned with the inter-personal variability of travel patterns. We synthesise the key analysis approaches as well as substantive findings and subsequently identify common trends and shortcomings and outline related directions for further research.

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Informa UK Limited , 2023. artikel-id 2251688
Nyckelord [en]
Travel patterns, public transport, smart card data, market segmentation, clustering, urban analytics
Nationell ämneskategori
Transportteknik och logistik
Identifikatorer
URN: urn:nbn:se:kth:diva-336990DOI: 10.1080/01441647.2023.2251688ISI: 001057517300001Scopus ID: 2-s2.0-85168903277OAI: oai:DiVA.org:kth-336990DiVA, id: diva2:1799582
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QC 20230922

Tillgänglig från: 2023-09-22 Skapad: 2023-09-22 Senast uppdaterad: 2023-09-22Bibliografiskt granskad

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Cats, Oded

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Totalt: 33 träffar
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