… In this work, the problem of path planning for an autonomous vehicle that moves on a … of a
driving policy based on reinforcement learning. In this way, the proposed driving policy makes …

… This paper reports results from experiments using Deep Reinforcement Learning on a
continuous-state, discrete-action autonomous driving simulator. We explore how Deep Neural …

… To generate automated human-like driving policies, we introduce a model-free, deep
reinforcement learning approach to imitate an experienced human driver’s behavior. We study a …

… Path tracking is an essential task for autonomous vehicles (… vehicle dynamic problem is
still challenging today, deep … of using deep reinforcement learning (DRL) for vehicle control …

… autonomous vehicles to improve the transportation system efficiency in such intersections.
In our solution, two connected autonomous vehicles (… by a deep reinforcement learning (DRL) …

… Abstract—This paper presents a predictive controller for longitudinal motion of automated
vehicles based on Deep Reinforcement Learning. It uses advance information about future …

… We use reinforcement learning and deep reinforcement learning interchangeably in this
paper because deep reinforcement learning is the major trend of reinforcement learning. …

… Then, we assessed driving risk by a probabilistic model with position uncertainty. This
model was integrated into deep reinforcement learning (DRL) to find strategies with minimum …

… Therefore, we establish the environment for autonomous driving on rough pavements.
The key components of the environment are rough pavements, dynamic speed limit, AV’s …

… for Reinforcement Learning and Deep Reinforcement Learning are introduced. Those
mechanisms are useful for our Survival-Oriented Reinforcement Learning (SORL) model. …