Given the recent advances in computer vision, image processing and control systems, self-
driving vehicles has been one of the most promising and challenging research topics …

This paper investigates the vision-based autonomous driving with deep learning and
reinforcement learning methods. Different from the end-to-end learning method, our method …

This paper investigates the vision-based autonomous driving with deep learning and
reinforcement learning methods. Different from the end-to-end learning method, our method …

This paper presents a novel model-reference reinforcement learning algorithm for the
intelligent tracking control of uncertain autonomous surface vehicles with collision …

Lane keeping assist (LKA) is an autonomous driving technique that enables vehicles to
travel along a desired line of lanes by adjusting the front steering angle. Reinforcement …

Vision-based sensors are widely used in lateral control of autonomous vehicles, but the
large computational cost of the visual algorithms often induces uneven time delays. In this …

Reinforcement Learning (RL) has been employed in many applications of robotics and has
steadily been gaining traction in the field of Autonomous Driving (AD). This paper proposes …

Abstract Nowadays, Artificial Intelligence (AI) is growing by leaps and bounds in almost all
fields of technology, and Autonomous Vehicles (AV) research is one more of them. This …

Autonomous driving has the potential to revolutionize mobility and transportation by
reducing road accidents, alleviating traffic congestion, and mitigating air pollution. This …

This letter studies the trajectory tracking and motion control problems of unmanned ground
vehicles (UGVs). A model predictive control and robust control (MPC-RC) framework for …