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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    Title :

    Identifying human mobility patterns using smart card data


    Contributors:
    Cats, Oded (author)

    Published in:

    Transport Reviews ; 44 , 1 ; 213-243


    Publication date :

    2024-01-02


    Size :

    31 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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