Modelling Driver Assitance Systems by Optimal Control

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 put forward a receding horizon control framework to model driver assistance systems. The accelerations of automated vehicles are determined 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)systems. The proposed ACC model characteristics are investigated analytically, with focus on equilibrium solutions and stability properties. The proposed ACC model is unconditionally locally stable. By careful tuning of parameters, the ACC model generates similar stability characteristics as human driver models.

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