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Author

A. Khazari

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Open access Sep 2026

A Multi-Agent Reinforcement Learning Framework for Adaptive Traffic Signal Control in Real Urban Networks: Simulation, Performance Analysis, and Statistical Evaluation

Urban traffic congestion continues to pose a significant challenge for modern cities, calling for intelligent traffic signal control (TSC) strategies able to coordinate multiple interconnected intersections under dynamic traffic conditions. To address this challenge, we propose a Hybrid Q-learning–SARSA–Monte Carlo Mul...

Azzeddine Ben Moussa, A. Khazari · 0 citations
Open access Aug 2026

Optimizing Traffic Signal Control Using Reinforcement Learning Methods: Hybrid Approach

A hybrid reinforcement learning approach for traffic signal control that combines the complementary learning mechanisms of Q-learning, SARSA, and Monte Carlo algorithms to improve both learning efficiency and control performance is proposed.

Azzeddine Ben Moussa, A. Khazari · 0 citations

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