Trajectory Planning for Off-road Autonomous Driving

Sammanfattning: The thesis develops a trajectory planner which operates in a formula racing scenario. The proposed trajectory planner gives time-optimal off-road trajectory planning solutions and generates sequences of control signals for the vehicle to follow the trajectory. Outputs of the trajectory planner are time-optimal trajectory, steering angle, resultant force of brake and throttle. The trajectory planner is designed to have two modes, the Exploring mode which is based on Rapidly-exploring Random Tree (RRT), and the optimization mode which is built upon optimal Rapidly-exploring random tree (RRT'). The exploring mode can generate a valid and safe trajectory in real  time, but the solution is not optimal; optimization mode gives optimal trajectories but it can only do offline planning. The system structure makes it possible that the exploring mode keeps running while the optimization mode runs in the background; once the optimization process is complete, the vehicle could then follow the optimal trajectory. A local trajectory planning method which considers the constraint of off-road vehicle dynamics is designed and integrated in the planner. System performance is evaluated by simulations on a racing track. Many aspects including time optimality, vehicle stability have been taken into account. A new, fast, local steering method has been proposed; the method generates trajectory based on random input. By a more efficient implementation of the planner in the future, for example by using parallel computing, the optimization mode is promising for real-time trajectory generation.