ALINEA, a local feedback ramp-metering strategy, has been shown to be a remarkably simple, highly efficient and easy application. This paper presents a microscopic simulation-based method to optimize the operational parameters of the algorithm, as an alternative to the difficult task of fine-tuning them in real-world testing. Four parameters, including the update cycle of the metering rate, a constant regulator, the location and desired occupancy of the downstream detector station, are considered. A genetic algorithm that searches the optimal combination of parameter values is employed. Simulation results show that the genetic algorithm is able to find a set of parameter values that can optimize the performance of the ALINEA algorithm.


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    Titel :

    GA-based parameter optimization for the ALINEA ramp metering control


    Beteiligte:
    Xu Yang, (Autor:in) / Lianyu Chu, (Autor:in) / Recker, W. (Autor:in)


    Erscheinungsdatum :

    01.01.2002


    Format / Umfang :

    418240 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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