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Trajectory planning and tracking for autonomous vehicles navigation

Abstract : In this thesis, the trajectory planning and the control of autonomous vehicles are addressed. As a first step, a multi-body modeling technique is used to develop a four wheeled vehicle planar model. This technique considers the vehicle as a robot consisting of articulated bodies. The geometric description of the vehicle system is derived using the modified Denavit Hartenberg parameterization and then the dynamic model of the vehicle is computed by applying a recursive method used in robotics, namely Newton-Euler based Algorithm. The validation of the developed vehicle model was then conducted using an automotive simulator developed by Oktal, the Scaner-Studio simulator. The developed vehicle model is then used to derive coupled control laws for the lateral and the longitudinal vehicle dynamics. Two coupled controllers are proposed in this thesis: In the first controller, the control is designed using Lyapunov control techniques while in the second one an Immersion and Invariance approach is used. Both of the controllers aim to ensure a robust tracking of the reference trajectory and the desired speed while taking into account the strong coupling between the lateral and the longitudinal vehicle dynamics. In fact, the coupled controller is a key step for the vehicle safety handling, especially in coupled maneuvers such as lane-change maneuvers, obstacle avoidance maneuvers and combined maneuvers in critical driving situations. The developed controllers were validated in simulation under Matlab/Simulink using experimental data. Subsequently, an experimental validation of the proposed controllers was conducted using a robotized vehicle (Renault-ZOE) present in the Heudiasyc laboratory within the Equipex Robotex project. Concerning the trajectory planning, a local planning method based on the clothoid tentacles method is developed. Moreover, a maneuver planning strategy focusing on the overtaking maneuver is developed to improve and complete the local planning approach. The local and the maneuver planners are then combined in order to establish a complete navigation strategy. This strategy is then validated using the developed robotics vehicle model and the Lyapunov based controller under Matlab/Simulink.
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Submitted on : Friday, March 9, 2018 - 2:56:09 PM
Last modification on : Thursday, October 3, 2019 - 9:45:52 AM
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  • HAL Id : tel-01727720, version 1


Alia Chebly. Trajectory planning and tracking for autonomous vehicles navigation. Automatic Control Engineering. Université de Technologie de Compiègne, 2017. English. ⟨NNT : 2017COMP2392⟩. ⟨tel-01727720⟩



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