Highlights New modelling framework for driver support systems based on optimal control theory. An optimal Adaptive Cruise Control (ACC) model with human-like behaviour. A novel Cooperative ACC (C-ACC) model that captures vehicle–vehicle collaborations. Insights into the resulting capacity and traffic stability of ACC and C-ACC models.

    Abstract Driver assistance systems support drivers in operating vehicles in a safe, comfortable and efficient way, and thus may induce changes in traffic flow characteristics. This paper puts forward a receding horizon control framework to model driver assistance and cooperative systems. The accelerations of automated vehicles are controlled to optimise a cost function, assuming other vehicles driving at stationary conditions over a prediction horizon. The flexibility of the framework is demonstrated with controller design of Adaptive Cruise Control (ACC) and Cooperative ACC (C-ACC) systems. The proposed ACC and C-ACC model characteristics are investigated analytically, with focus on equilibrium solutions and stability properties. The proposed ACC model produces plausible human car-following behaviour and is unconditionally locally stable. By careful tuning of parameters, the ACC model generates similar stability characteristics as human driver models. The proposed C-ACC model results in convective downstream and absolute string instability, but not convective upstream string instability observed in human-driven traffic and in the ACC model. The control framework and analytical results provide insights into the influences of ACC and C-ACC systems on traffic flow operations.


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    Titel :

    Modelling supported driving as an optimal control cycle: Framework and model characteristics


    Beteiligte:
    Wang, Meng (Autor:in) / Treiber, Martin (Autor:in) / Daamen, Winnie (Autor:in) / Hoogendoorn, Serge P. (Autor:in) / van Arem, Bart (Autor:in)


    Erscheinungsdatum :

    2013-06-30


    Format / Umfang :

    17 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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