The frequent traffic congestion on the highways has necessitated the formulation of a suitable traffic control strategy that reduces transportation time. The main objective of any highway traffic control strategy is to regulate the traffic flow in such a manner that the participating vehicles can travel as fast as possible without any congestion. To accommodate this goal and to maintain a steady stream of vehicles on the highway, this work proposes a Model Predictive based Sliding mode Cooperative and Integrated Control that produces a real-time applicable, optimal, robust, and stable control command. In this sense, the traffic control problem is reformulated as a second-order nonlinear affine state space model, and then, the resulting control signal is derived via Model Predictive based Sliding Model Control (MPSMC). The proposed method delivers better results w.r.t established strategies in terms of Total Time Spent (TTS) and computation time. Furthermore, the Utilization Cost Function has been introduced in this work, rather than TTS, and it has been applied to the optimization problem of MPSMC to better utilize the existing characteristics of the highway, which has yielded a smoother traffic flow.


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    Titel :

    Model Predictive Sliding Mode Control of Highway Traffic Flow: Cooperative and Integrated Approach


    Weitere Titelangaben:

    Int. J. ITS Res.


    Beteiligte:


    Erscheinungsdatum :

    01.04.2024


    Format / Umfang :

    13 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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