D. C. A. Reddy

Edge-Assisted Multi-Agent Deep Reinforcement Learning for Emergency and Emission-Aware Traffic Signal Control

Urban traffic signal control must reduce congestion, prioritize emergency vehicles, and limit environmental impact under dynamic traffic conditions. Fixed-time control cannot adapt effectively to such variations. Existing learning-based methods have shown promising results, but most of them do not jointly address emerg...