… Abstract—Academic research in the field of autonomous vehicles has reached high … this
article describes one of these fields, Deep Reinforcement Learning (DRL). The paper provides …

… ABSTRACT Autonomous driving is a promising technology to reduce traffic … deep reinforcement
learning (DRL)-enabled decision-making policy is constructed for autonomous vehicles …

… of Deep Reinforcement Learning to handle intersection problems. Using recent advances in
Deep … of our current deep reinforcement learning system point to future research directions. …

… Our approach aims to develop an agent that generates autonomous vehicle control based
on Deep Reinforcement Learning algorithm that solves a MDP. The following sections show …

… hybrid Deep Reinforcement learning and Genetic algorithm for Smart-Platooning (DRG-SP)
the AVs. The leverage of the deep reinforcement … Algorithm in Deep Reinforcement learning …

… autonomous driving systems running in traffic with both ADVs and HDVs, we mainly focus
on modeling vehicle interactions based on deep reinforcement … of surrounding vehicles, and …

… a control approach for autonomous vehicles based on deep reinforcement learning. A …
to control a fullsize research vehicle. For this, the autonomous exploration of a parking lot is …

… needs to be considered for autonomous vehicles (AVs). To … on deep reinforcement learning
to find a risk-aware driving decision strategy with the minimum expected risk for autonomous …

… Further, multiple variants of this work were presented that allowed the incorporation of
nonautonomous vehicles (FCFS-light) [2], [35], as well as emergency vehicles such as …

… , thus, to propose a novel adversarial deep reinforcement learning (RL) framework that aims
… from intravehicle sensors such as camera, radar, RSSs, and intervehicle beaconing. We …