This study proposes a path-tracking algorithm based on feed-forward (preview distance control) and feedback (LQR, linear quadratic regulator) controllers to reduce heading angle errors and lateral distance errors between a predefined path and an autonomous vehicle. The main objective of path-tracking is to generate control commands to follow a predefined path. The feed-forward control is applied to solve heading angle errors and lateral distance errors in the trajectory caused by curvatures of the road by controlling the steering angle of the vehicle. An LQR was applied to decrease the errors caused by environmental and external disturbances. The proposed algorithm was verified by simulating the driving environment of an autonomous vehicle using a CARLA simulator. Safety and comfort were demonstrated using the test vehicle. The study also demonstrated that the tracking performance of the proposed algorithm exceeded that of other path-tracking algorithms, such as Pure Pursuit and the Stanley Method.

This paper proposes a simplified path-following control method for an Unmanned Surface Vessel (USV) considering towed Unmanned Underwater Vehicles (UUV). For dealing with an effective USV dynamic model, 1st order of the linear system with time delay and gain value are applied rather than applying a non-linear dynamic model, and it is identified with real vessel data from several straight and turning experiments. Then, USV attitude and velocity are controlled by multi-loop Proportional-Derivative (PD) and proportional controller. A USV guidance scheme is derived through a UUV guidance scheme to support autonomous navigation for towed UUV, and combination of cross track and Line of Sight (LOS) guidance is presented for adaptive path following. Finally, to validate the performance of the proposed USV path-following control method with respect to the towed UUV guidance scheme, the results of simulations are presented.