… Learning itself have been developed, and this article describes one of these fields, Deep
Reinforcement Learning (DRL… The paper describes vehicle models, simulation possibilities and …

… of the autonomous vehicle is obtained as … autonomous vehicle using reinforcement learning
techniques. Second, we collect a number of demonstrations from an expert driver and learn …

… and deployment of autonomous vehicles is the … autonomous vehicles in an accelerated
mode, without loss of unbiasedness. From naturalistic driving data, the background agents learn …

… all fields of technology, and Autonomous Vehicles (AV) research is one … Learning (DL) in
the control layer of an autonomous vehicle. More specifically, Deep Reinforcement Learning (…

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

… Abstract— We present a control approach for autonomous vehicles based on deep
reinforcement learning. A neural network agent is trained to map its estimated state to acceleration …

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

… stability guarantee for autonomous vehicles with limited … learning-based algorithm with the
stability guarantee is proposed to train policies for the motion planning of autonomous vehicles…

… reinforcement learning approach for robust lane change decision making of autonomous
vehicles… decision making behaviors of autonomous vehicles under policy constraints and …

… the vehicles… vehicles. A Composite Platoon Trajectory Planning Strategy (CPTPS) proposed
in [25], develops a trajectory plan for the leader vehicles and applies reinforcement learning …