This paper proposes a new modeling approach for network-wide on-line travel time estimation with inconsistent data from multiple sensor systems. It makes full use of both the available data from multiple sensor systems (on-line data) and historical data (off-line data). The first- and second-order statistical properties of the on-line data are investigated together with the data inconsistency issue to estimate network-wide travel times. The proposed model is formulated as a generalized least squares problem with non-linear constraints. A solution algorithm based on the penalty function method is adopted to solve the proposed model, whose application is illustrated by numerical examples using a local road network in Hong Kong.


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    Titel :

    Network-wide on-line travel time estimation with inconsistent data from multiple sensor systems under network uncertainty


    Beteiligte:
    Shao, Hu (Autor:in) / Lam, William H. K. (Autor:in) / Sumalee, Agachai (Autor:in) / Chen, Anthony (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    02.01.2018


    Format / Umfang :

    20 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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