An alternative approach to estimating aggregate traffic variables on freeways--spatial mean velocity and density--is presented. Vehicle arrival times at a given location on a roadway, typically a presence detector, are regarded as a point or counting Poisson process whose rate is a function of the state of the traffic at every instant of time. Moreover, the traffic state is modeled as a finite-state Markov chain. A sequential point process filter, optimum in the mean-squared error sense, is designed to estimate the state from observations of the vehicle arrival-time sequence. Different possibilities for incorporating potential additional information such as speed and headway are explored. Parameter values for the underlying Markov chain are obtained via a maximum likelihood estimator. Qualitative behavior of the proposed algorithms is studied with simulated traffic flow data from both macroscopic and microscopic models.


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    Titel :

    Estimation of Traffic Variables Using Point Processing Techniques


    Beteiligte:
    R. Lopez-Lopez (Autor:in) / P. K. Houpt (Autor:in)

    Erscheinungsdatum :

    1978


    Format / Umfang :

    80 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch




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