Developed an AI-based traffic light control system using Deep Reinforcement Learning and SUMO simulation to optimize traffic flow in urban intersections. The model dynamically adjusts signal timings based on real-time vehicle density, helping reduce waiting time and improve traffic throughput compared to fixed-timer systems. Built with Python and reinforcement learning algorithms for intelligent decision-making in smart city use cases.