… in machine learning. An … of autonomous vehicles based on reinforcement learning in V2X
environment are studied in this paper. First, the interactions between an autonomous vehicle …

… the operation of autonomous vehicles based on the … reinforcement learning (DRL)
algorithm is designed to learn … speed controls of autonomous vehicles on rough pavements. …

… (CAV) network can be defined as a set of connected vehicles … the dynamic number of agents
(vehicles) and the fast-growing … Therefore, we present a novel deep reinforcement learning-…

… of path planning for an autonomous vehicle that moves on a … of a driving policy based on
reinforcement learning. In this way, the … both by autonomous and manual driving vehicles are …

… learning capability of neural networks, data-driven-based methods including supervised
learning and reinforcement learning … learning are booming for the development of autonomous …

… In this review we cover the notions of reinforcement learning, … Reinforcement learning
methods were developed to handle … Autonomous vehicle stochastic control is large domain, and …

… Reinforcement learning (RL) methods have gained popularity in the field of motion planning
for autonomous vehicles … -based motion planners for autonomous vehicles. Configurability, …

… making for autonomous vehicles. This paper constructs a transfer deep reinforcement learning
(… cast into a left turn, right turn, and running straight for automated vehicles. The goal of the …

… the traffic and avoid congestion in scenarios where all vehicles behave autonomously. In
the first phase, we build a deep reinforcement learning-based intelligent traffic light module to …

… This work proposes a novel framework based on deep reinforcement learning for
benchmarking the behavior of collision avoidance mechanisms under the worst-case scenario of …