… to navigate safely through unsignaled intersections is a difficult task … Reinforcement Learning
to handle intersection problems. Using recent advances in Deep RL, we are able to learn …

… In this section, we explain the model defined for representing the occluded intersection
which is depicted in Fig. 1. This representation can be used by a rule-based or a …

… learning techniques on lane changing problems. The potential of deep reinforcement learning
in handling intersection … The main focus of this work is to deal with occluded intersections. …

… learning to predict occlusion segments, and optimal camera positions, while the other learns
to avoid occlusion using Reinforcement Learning. … The intersections of the object bounding …

… Fujimura, “Navigating occluded intersections with autonomous vehicles using deep
reinforcement learning,” in IEEE International Conference on Robotics and Automation (ICRA), 2018…

… a simple occlusion model that enables our agents to navigate intersections with occlusions
… various agents using Deep Reinforcement Learning on a small set of intersection layouts and …

… intersection navigation as a multi-task reinforcement learning problem and propose a unified
learning … Fujimura, “Navigating occluded intersections with autonomous vehicles using …

… Duerr, “Superhuman performance in gran turismo sport using deep reinforcement learning,”
… occluded intersections with autonomous vehicles using deep reinforcement learning,” in …

… Fujimura, “Navigating occluded intersections with autonomous vehicles using deep
reinforcement learning,” in 2018 IEEE International Conference on Robotics and Automation (ICRA). …

… An additional study with a simple occlusion model is … trained using a curriculum reinforcement
learning approach, we present a … curriculum-based reinforcement learning for autonomous …