Adaptive Traffic Signal Control at a Single Intersection Using Deep Reinforcement Learning: A SUMO-Based Comparative Study
Urban road networks lose a large amount of time and fuel to congestion at signalised intersections, and conventional fixed-time controllers cannot react to the changing and uneven traffic demand seen in practice. Reinforcement learning (RL), and in particular deep reinforcement learning (DRL), has been proposed as a wa...