… , and then applies physics-based raycasting and machine learning to generate realistic LiDAR
… Adversarial Objective: To induce autonomy system failures, we propose a combination of …

… multi-agent reinforcement learning (MARL) is especially … , we have in Table 1 mapped the
double merge scenario to … difference covers both Diversity and Safety. In Intersection, Agility …

… an action planning method to enable an autonomous car to merge into a roundabout. While
… inverse reinforcement learning approach to optimize the planning for autonomous vehicles …

… of machine learning approaches for autonomous driving has … that combines the most
promising elements of the end-to-end … For comparing the safety of autonomous driving solutions, …

… time, how to merge AVs into human drivers’ traffic ecology and … Since the machine learning
algorithm is developed based on … , “Enabling safe autonomous driving in realworld city traffic …

… Further, there will be safety concerns if RL control is switched … Then all hidden units are
combined and input to a LSTM … complex systems, and robotics and automated vehicles. He was a …

… poses sample efficiency and safety challenges. Moreover, in … We show that methods that
combine RL with prior information… Different forms of learning have enabled autonomous driving …

… In recent years, the deep reinforcement learning method has … Deep reinforcement learning
(DRL) combines deep learning … for self-driving cars to realize safe and autonomous driving in …

… by applying ORCA-F, and the combination of IL and RL is not the … avoidance via deep
reinforcement learning for safe and … lateral control for autonomous driving [application notes],” …

… algorithms are essential for safe and efficient robot operation … A fundamental challenge
in autonomous vehicle operation is … combining the benefits of both reactive- and trajectory-based …