Trajectory Following Control for Automated Driving

In the contribution, a model predictive trajectory tracking approach is presented. Due to the utilization of an accurate prediction model, which considers not only the vehicle dynamics but also the limited actuator dynamics, the approach can be used even in emergency collision avoidance systems. The approach explicitly predicts a trajectory set for defined control inputs. Out of the set, the trajectory which is closest to the reference is selected. Two different objective functions are defined, each of them selecting the optimum input variable for trajectory tracking. On the one hand, the selection is based on the predicted position trajectories and, on the other hand, on the speed and yaw rate of the trajectory set. The evaluation is carried out in the simulation with a vehicle model for which different error sources, like sensor errors, sensor noise, and static friction are modeled using data from a real vehicle. This development method allows a direct and fast transferability into the real test vehicle.