Bluetooth data sets allow a direct estimation of travel times across sensor pairs; however, the resulting estimations contain noise because of missed detection rate and alternative paths between sensors. Additionally, although Bluetooth data sets allow tracking of vehicles across sensors, they do not provide an exact path (i.e. a sequence of traffic sections). Estimating vehicle paths from Bluetooth records is not a straightforward task. This paper proposes a joint method to simultaneously infer vehicle paths and travel times using Bluetooth records. The methodology is applied in a case study of Bluetooth measurements in Brisbane, Australia. The results are validated against travel time observations, which are collated by creating a testing set out of the whole data set. Travel time estimates are robust to the changes in the size of the available measurements, and the proposed model significantly outperforms a naive model where travel times are estimated via direct matching.


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    Titel :

    Joint estimation of paths and travel times from Bluetooth observations


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2021-01-01


    Format / Umfang :

    19 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt





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