The IEEE International Conference on Intelligent Transportation Systems, Maui, USA.
This work deals with the design of a supervisory module for the motion control of autonomous vehicles. The supervisor’s goal is to monitor the behavior of a trajectory tracking controller (TTC), introducing corrective control actions to prevent violations of safety and input constraints. It relies on the combination of control barrier functions and optimization methods, and considers Lyapunov-based constraints and costs to penalize performance degradation due to supervisor’s corrective actions. Simulation results of a collision avoidance scenario demonstrate the effectiveness of the proposed supervised TTC.
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