Identifying human mobility patterns using smart card data

Oded Cats

Document Type

Journal Article

Publication Date

2024

Subject Area

literature review - literature review, technology - passenger information, technology - ticketing systems, place - urban, ridership - behaviour

Keywords

Travel patterns; public transport, smart card data, market segmentation, clustering, urban analytics

Abstract

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.

Rights

Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.

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