Model Based Trajectory Planning for Highly Automated Road Vehicles

The aim of this paper is to present a local trajectory planning method based on nonlinear optimization that is able to generate a dynamically feasible, comfortable and customizable trajectory for highly automated road vehicles. The presented algorithm is able to consider the nonholonomic dynamics of wheeled vehicles and ensures the dynamical feasibility of the planned trajectory by the model-based prediction of the vehicle's motion. The behavior of the vehicle is simulated with closed loop trajectory tracking control which allows to generate not only the trajectory of the vehicle but also the reference signal inputs for the controllers. The direct planning of the reference signals enables the vehicle to run exactly on the generated trajectory and eliminates the delays related to the inertia of the system.