The development of sustainable mobility solutions calls for significant advances in travel demand data collection beyond the long-term static planning data usually available at planning agencies. This paper proposes a combined clustering, regression, and gravity model to estimate an origin-destination (OD) matrix for non-commuting trips based on Foursquare user check-in data in the Chicago urban area. The estimated OD matrix is found to be similar to the ground-truth OD matrix obtained from CMAP (Chicago Metropolitan Agency for Planning). The potential applications for generating day-of-the-week and dynamic bihourly OD patterns from Foursquare data are also illustrated.


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    Title :

    Origin-Destination Estimation for Non-Commuting Trips Using Location-Based Social Networking Data




    Publication date :

    2015




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English



    Classification :

    BKL:    55.80 / 55.80 Verkehrswesen, Transportwesen: Allgemeines



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