Oct 9, 2020 · Traffic signal control is one of the most efficient methods for urban traffic management, providing a smoother and more secure traffic flow at every intersection.

Nov 28, 2023 · Traffic signals coordinate the traffic movements at the intersection, and a smart traffic signal control algorithm is the key to transportation efficiency. Traffic signal control remains an active research topic because of the high complexity of the problem.

May 1, 2024 · Optimizing signal timing at signalized intersections is a key approach to alleviate traffic congestion and improve traffic efficiency, as signalized intersections serve as major bottlenecks in urban traffic.

In this tutorial, we first introduce the formulation of traffic light control problems under RL, and then classify and discuss the current RL control methods from different aspects: agent formulation, policy learning approach, and coordination strategies.

Jun 4, 2024 · We present the traffic signal control problem as a Markov Decision Process (MDP) and employ the reinforcement learning algorithm (Q-learning and DQN) to acquire a dynamic and effective traffic signal control strategy.

Through the use of advanced driver assistance, vehicles in a convoy can keep shorter distances from each other, thus decreasing energy consumption and traffic jams. However, reliable and low-latency communications are a vital prerequisite for such systems.

Jan 1, 2023 · In addition, the value-based DRL algorithms outperform the policy-based algorithm and traditional TSC control methods. The findings of this research would provide insights and guidance for transport engineers to design an efficient …

May 8, 2017 · In this paper, we propose a deep reinforcement learning algorithm that automatically extracts all useful features (machine-crafted features) from raw real-time traffic data and learns the optimal policy for adaptive traffic signal control.

Abstract—Adaptive traffic signal control, which adjusts traffic signal timing according to real-time traffic, has been shown to be an effective method to reduce traffic congestion.

This research develops and implements a learning-based algorithm for signal control that allows signal controller agents to share information with its neighbor controllers through I2I communication within CV environment.