Highlights Model predictive schemes for traffic control in large freeway systems are proposed. The optimal control problems to be solved have a mixed-integer linear structure. Event-triggered MPC schemes are considered to reduce the computational effort. The performance of the proposed approach is assessed via simulation.

    Abstract Objective of the paper is to define a new freeway traffic control approach based on the Model Predictive Control methodology. The control strategy adopted is ramp metering, which is able to reduce the flow entering the mainstream from the on-ramps so as to enforce traffic regularity. To determine the ramp metering actions, an innovative MPC scheme is proposed and is characterized by two major novel aspects. First of all, the finite horizon problem to be solved has a mixed-integer linear form, so that efficient solvers can be used to find the optimal solution. Secondly, in order to reduce the number of computations, the proposed MPC scheme is of event-triggered type, i.e. the control law is not updated at each time step but only when a given set of conditions is verified. The proposed scheme is assessed in the paper via simulation showing its effectiveness in different traffic scenarios.


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    Titel :

    Event-triggered model predictive schemes for freeway traffic control


    Beteiligte:
    Ferrara, Antonella (Autor:in) / Sacone, Simona (Autor:in) / Siri, Silvia (Autor:in)


    Erscheinungsdatum :

    2015-01-22


    Format / Umfang :

    14 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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