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This paper presents design and experimental validation of a vehicle lateral controller for autonomous vehicle based on a higher-order sliding mode control. We used the super-twisting algorithm to minimize the lateral displacement of the autonomous vehicle with respect to a given reference trajectory. The control input is the steering angle and the output is the lateral displacement error. The particularity of such a strategy is to take advantage of the robustness of the sliding mode controller against nonlinearities and parametric uncertainties in the model, while reducing chattering, the main drawback of first order sliding mode. To validate the control strategy, the closed-loop system simulated on Matlab-Simulink has been compared to the experimental data acquired on our vehicle DYNA, a Peugeot 308, according to several driving scenarios. The validation shows robustness and good performance of the proposed control approach.

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Abstract-The work presented in this paper focuses on reactive local trajectory planning which plays an essential role for future autonomous vehicles. The challenge is to avoid obstacles in respect to road rules while following a global reference trajectory. The planning approach used in this work is the method of clothoid tentacles generated in the egocentered reference frame related to the vehicle. Generated tentacles in a egocentered grid represent feasible trajectories by the vehicle, and in order to choose the right one, we formulate the problem as a Markov Decision Process.

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