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

… Intersection Management (AIM) systems, which operate at the level of traffic intersections and
manage the … However, Deep Reinforcement Learning (DRL) can provide advanced control …

… traffic intersection management problem, we propose a reinforcement learning (RL) based
… architecture and a novel RL algorithm coined multi-discount Q-learning. In multi-discount Q-…

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

… to-end autonomous intersection control agent, based on Deep Reinforcement Learning (DRL)…
Our DRL traffic intersection control agent configures the traffic signal regimes based solely …

… intersections, optimising solely for efficiency can negatively impact vehicle fairness. This study
addresses this issue by proposing a deep reinforcement learning … -world intersection and …

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

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

… limitations of conventional Reinforcement Learning methods such as … Reinforcement
Learning methods, known as Trust Region Policy Optimization, to tackle intersection management …

… To proceed towards this vision, in this paper, we develop a traffic flow management model …
using Deep Reinforcement Learning (DRL) to optimize traffic flow on road intersections during …