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Identifying human mobility patterns using smart card data
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning. 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 (English)In: Transport reviews, ISSN 0144-1647, E-ISSN 1464-5327, article id 2251688Article in journal (Refereed) 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.

Place, publisher, year, edition, pages
Informa UK Limited , 2023. article id 2251688
Keywords [en]
Travel patterns, public transport, smart card data, market segmentation, clustering, urban analytics
National Category
Transport Systems and Logistics
Identifiers
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
Note

QC 20230922

Available from: 2023-09-22 Created: 2023-09-22 Last updated: 2023-09-22Bibliographically approved

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Cats, Oded

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf