  Abstract: we present a framework for robust autonomous driving motion
planning system in urban environments which includes trajectory refinement,
trajectory interpolation, avoidance of static and dynamic obstacles, and
trajectory tracking. Given road centerline, our approach smoother the original
line via cubic spline. Fifth order Bezier curve is then used to generate more
human-like trajectories that guarantee at least second order continuity and
curvature continuity. Dynamic trajectory planning task is decoupled into
lateral spatial and longitudinal velocity planning problems. A bunch of
candidate trajectory sets are generated and evaluated by an object function
which considers kinematic feasibility, trajectory smoothness, driving comfort
and collision-checking. Meanwhile, an LQG controller is used to generate
longitudinal velocity profile to ensure safety and comfort. After that, spatial
and velocity profiles are transformed into commands executed by lateral
steering and longitudinal acceleration controllers. This framework is validated
within a simulation study and has been deployed on our autonomous vehicle shown
in Fig.1 that has travelled thousands of miles in urban environments.
