… dense traffic can be challenging for autonomous vehicles. An … vehicle will only try to merge
in front of cooperative drivers. In order to learn such a behavior through reinforcement learning…

… We use reinforcement learning and deep reinforcement learning … reinforcement learning is
the major trend of reinforcement … of an autonomous vehicle using reinforcement learning,” in …

… vehicle and other obstacles and a reinforcement learning (RL) algorithm to navigate the
self-driving vehicle. … on inverse reinforcement learning for autonomous vehicle decisionmaking,” …

… autonomous vehicle technologies, the use of such eco-driving technologies may increase
as the driver's interventions in vehicle driving decrease; thus, these autonomous vehicles …

… deep reinforcement learning to learn driving policies: [21] learned a safe multiagent model
for autonomous vehicles on … In this work, A deep reinforcement learning (DRL) with a novel …

… the key guiding principles for autonomous vehicles. Manually … , learned through means of
reinforcement learning (RL) suffer … recent advances in imitation learning and that can generate …

… -speed drift control through manifold corners for autonomous vehicles, we propose a closed-…
) to control the steering angle and throttle of simulated vehicles. The error-based state and …

… vehicles (AVs) and humans are considered. Advanced techniques in reinforcement learning
(… finding the optimal trajectories of autonomous vehicles that maximize the specified reward/…

… on robotic systems such as autonomous driving and industrial … reinforcement learning,
control, deep learning, autonomous … vehicles and driver assistance, reinforcement learning and …

… In this study, autonomous vehicles in coordination learn how to behave in a highway scenario.
Two distinct coordination graph models, identity-based dynamic coordination and position…