The state-of-the-art decision and planning approaches for autonomous vehicles have
moved away from manually designed systems, instead focusing on the utilisation of large …

Deep Learning and back-propagation have been successfully used to perform centralized
training with communication protocols among multiple agents in a cooperative environment …

Deep reinforcement learning (DRL) is a machine learning method based on rewards, which
can be extended to solve some complex and realistic decision-making problems …

Numerous accidents and fatalities occur every year across the world as a result of the
reckless driving of drivers and the ever-increasing number of vehicles on the road. Due to …

In this survey, we systematically summarize the current literature on studies that apply
reinforcement learning (RL) to the motion planning and control of autonomous vehicles …

We demonstrate the first application of deep reinforcement learning to autonomous driving.
From randomly initialised parameters, our model is able to learn a policy for lane following in …