A method is presented for combining two previously proposed algorithms for path-planning and dynamic steering control into a computationally feasible scheme for real-time feedback control of autonomous vehicles in uncertain environments. In the proposed approach to vehicle guidance and control, Path Relaxation is used to compute critical points along a globally desirable path using a priori information and sensor data. Generalized potential fields are then used for local feedback control to drive the vehicle along a collision-free path using the critical points as subgoals. Simulation results are presented to demonstrate the control scheme.