AI for Dynamic Traffic Flow Optimization in Smart Cities

Sai Teja Boppiniti

Abstract


Managing traffic flow is a critical challenge in urban areas. This paper presents an AI-driven system for dynamic traffic flow optimization in smart cities. The system employs reinforcement learning algorithms to analyze real-time traffic data from IoT sensors and optimize traffic signal timings. The approach is validated in simulated urban environments, demonstrating reduced congestion and travel times. The research emphasizes the role of AI in improving urban mobility, reducing emissions, and enhancing the quality of life in smart cities.

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