Dec 31, 2022 · This study introduces a two-stage approach to compress the network, maintaining performance. Firstly, we identify a compact network via a ...
Abstract—Reinforcement learning (RL)-based traffic signal control (TSC) optimizes signal switches through RL agents, adapting to intersection updates.
Jun 18, 2024 · This paper seeks traffic signal control policies which maximise long-run network throughput when demand is within network capacity and also when ...
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Toward Efficient Traffic Signal Control: Smaller Network Can Do More. S Li, H Mei, J Li, H Wei, D Xu. 2023 62nd IEEE Conference on Decision and Control (CDC) ...
Toward Efficient Traffic Signal Control: Smaller Network Can Do More ... Traffic signal control is essential for transportation efficiency in road networks.
Mar 29, 2018 · In this paper, we study how to decide the traffic signals' duration based on the collected data from different sensors and vehicular networks.
Traffic signal control is essential for transportation efficiency in road networks. It has been a challenging problem because of the complexity in traffic ...
Inefficient traffic control may cause numerous problems such as traffic congestion and energy waste. This paper proposes a novel multi-agent reinforcement ...
Jun 19, 2024 · Today, urban TS are typically optimized using fixed-time control (FTC), induction control, and Adaptive Traffic Signal Control (ATSC) methods.
This work proposes a decentralized Model Predictive Control (MPC) strategy for the minimization of the queue length in a multi-intersection road network.
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