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Consistency and stability of hierarchical planning and control systems for autonomous driving

Abstract : Autonomous vehicles are believed to reduce the number of deaths and casualties on the roads while improving the traffic efficiency. However, before their mass deployment on open public roads, their safety must be guaranteed at all time.Therefore, this thesis deals with the motion planning and control architecture for autonomous vehicles and claims that the intention of the vehicle must match with its actual actions. For that purpose, the kinematic and dynamic feasibility of the reference trajectory should be ensured. Otherwise, the controller which is blind to obstacles is unable to track it, setting the ego-vehicle and other traffic participants in jeopardy. The proposed architecture uses Model Predictive Control based on a kinematic bicycle model for planning safe reference trajectories. Its feasibility is ensured by adding a dynamic constraint on the steering angle which has been derived in this work in order to ensure the validity of the kinematic bicycle model. Several high-frequency controllers are then compared and their assets and drawbacks are highlighted. Finally, some preliminary work on model-free controllers and their application to automotive control are presented. In particular, an efficient tuning method is proposed and implemented successfully on the experimental vehicle of ENSIAME in collaboration with the laboratory LAMIH of Valenciennes.
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Submitted on : Thursday, April 11, 2019 - 3:38:10 PM
Last modification on : Wednesday, November 17, 2021 - 12:31:06 PM


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  • HAL Id : tel-02096788, version 1


Philip Polack. Consistency and stability of hierarchical planning and control systems for autonomous driving. Automatic. Université Paris sciences et lettres, 2018. English. ⟨NNT : 2018PSLEM025⟩. ⟨tel-02096788⟩



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