Outils de pré-calibration numérique des lois de commande de systèmes de systèmes : application aux aides à la conduite et au véhicule autonome

Abstract : This thesis deals with the tuning of the new Advanced Driving Assistance Systems (ADAS). The development of these systems has become nowadays a strategic line of research for the automotive industry towards the conception of safer and fuel-efficient vehicles.This thesis contributes to a multi-criterion, multi-modeland multi-scenario methodological vision of the tuning process. It is presented through a specific application of the tuning of the Lane Centering Assistance (LCA). It relies on vehicle and environment’s dynamical models of adequate complexity in the aim of formalizing and managing, in a H2/H∞ framework, the trade-off between performance, comfort and robustness. The formulated criteria are easy to compute and defined in a way to be understandable, closely linked to practical specifications. The whole methodology is driven by the research of a pertinent trade-off between realism (being as closest as possible to reality) and complexity (quick evaluation of the criterion). The efficiency and the robustness of the approach is demonstrated through high-fidelity simulations and numerous tests on real vehicles.
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Simon Éliakim Mustaki. Outils de pré-calibration numérique des lois de commande de systèmes de systèmes : application aux aides à la conduite et au véhicule autonome. Automatique. Ecole nationale supérieure Mines-Télécom Atlantique, 2019. Français. ⟨NNT : 2019IMTA0142⟩. ⟨tel-02297892⟩

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