… of commercial vehicles, a decision-making method for rear anti-collision based on deep
reinforcement … 1, an autonomous commercial vehicle (the ego vehicle) is driving in the multi-lane …

… 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 …

… Deep Reinforcement … in commercial vehicles like Mobileye’s path planning system.
However, a vast majority of work on DRL is focused on toy examples in controlled synthetic car …

… From 1990 to 2017, the average kilometers per liter (km/L) for all light-duty vehicles in the
US was increased by 18% [1]. Nevertheless, in the same period, greenhouse gas emission …

… for autonomous driving, we provide a short overview of deep reinforcement learning and …
A robot car that drives autonomously is a long-standing goal of Artificial Intelligence. Driving …

… 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 …

… This review summarises deep reinforcement learning (DRL) … in real world deployment of
autonomous driving agents. It also … Autonomous vehicle stochastic control is large domain, and …

… In simulations, we used the commercial software PreScan which models vehicle dynamics
in real time [15]. We generated the environment in order to train the DQN by simulating the …

… Then, we focus on the three types of physical autonomous systems, ie, autonomous robots,
smart vehicles, and smart grid, in Section IV-C, IV-D, and IV-E, respectively. Note that some …

… by the ACC in connected autonomous vehicles by utilizing Reinforcement Learning (RL), a
… we focus on Deep Reinforcement Learning (DRL), which incorporates deep neural networks …