Safe Motion Planning for Autonomous Driving

Self-driving cars have the potential to revolutionize transportation by making it cheaper, safer, and more efficient. In this thesis we describe a novel motion planning system, which translates high-level navigation goals into low-level actions for controlling a vehicle. Specifically, the motion planning system is responsible for choosing at each time step an appropriate velocity and steering angle, which can then be implemented by the driving hardware or simulator. Our planner is able to compute a safe and efficient trajectory in a dynamic environment while staying within its lane and avoiding obstacles.