BIROn - Birkbeck Institutional Research Online

    A high-precision heuristic model to detect home and work locations from smart card data

    Sari Aslam, Nilufer and Cheng, T. and Cheshire, J. (2019) A high-precision heuristic model to detect home and work locations from smart card data. Geo-spatial Information Science 22 (1), pp. 1-11. ISSN 1009-5020.

    48503.pdf - Published Version of Record
    Available under License Creative Commons Attribution.

    Download (2MB) | Preview


    Smart card-automated fare collection systems now routinely record large volumes of data comprising the origins and destinations of travelers. Processing and analyzing these data open new opportunities in urban modeling and travel behavior research. This study seeks to develop an accurate framework for the study of urban mobility from smart card data by developing a heuristic primary location model to identify the home and work locations. The model uses journey counts as an indicator of usage regularity, visit-frequency to identify activity locations for regular commuters, and stay-time for the classification of work and home locations and activities. London is taken as a case study, and the model results were validated against survey data from the London Travel Demand Survey and volunteer survey. Results demonstrate that the proposed model is able to detect meaningful home and work places with high precision. This study offers a new and cost-effective approach to travel behavior and demand research.


    Item Type: Article
    Keyword(s) / Subject(s): Smart card data; activity location modeling; heuristic primary location model; home and work locations; human mobility pattern; urban activity pattern.
    School: Birkbeck Faculties and Schools > Faculty of Humanities and Social Sciences > School of Social Sciences
    Depositing User: Nilufer Sari Aslam
    Date Deposited: 14 Jul 2022 10:37
    Last Modified: 02 Aug 2023 18:17


    Activity Overview
    6 month trend
    6 month trend

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item Edit/View Item