… need to cross an intersection. In this work, we propose an innovative management
system called Deep Reinforcement Learning-based Autonomous Intersection Management (DRLAIM) …

… A key component is Autonomous Intersection Management (AIM) systems, which operate
at the level of traffic intersections and manage the right-of-way of AVs, improving flow and …

… autonomous traffic intersection management problem, we propose a reinforcement learning
(… Broggi, “End-to-end intersection handling using multi-agent deep reinforcement learning,” …

… recommend deep reinforcement learning-inspired autonomous intersection management
(… are the priority assignment model, the intersection-control model learning, and safe brake …

… , etc.) crossing the intersection to eliminate accidents due to … state of all AVs at the intersection
and adapt its strategy in a … a novel latency-aware deep reinforcement learning-based AIM …

… vector specifying the presence of a vehicle at the intersection. Along with this Boolean vector,
some … We believe that certain aspects of SUMO (such as its random incident management …

… -systems, Autonomous Intersection Management (AIM) has … trajectory of connected vehicles
around intersections. Most of the … solutions using deep reinforcement learning (deep RL) that …

… reinforcement learning-based traffic signal control. In brief, this thesis found that reinforcement
learning algorithms could potentially be used to control signalized intersections in mixed …

… Intersection Management (AIM) systems. AIMs present a new paradigm for CAV control in
future cities, taking control of CAVs in scenarios where cooperation is necessary and allowing …

… Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates.
In IEEE International Conference on Robotics and Automation, pages 3389–3396, 2017. …