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Dynamic Traffic Light Control Algorithm by prajwalp22xhdhhdhd is a document available to read on EtoBox.

This paper presents a convolutional neural network-based signal distribution control algorithm aimed at optimizing traffic signal timing to alleviate congestion in urban areas. It utilizes reinforcement learning techniques, specifically Deep Q-learning, to adaptively manage traffic flow based on real-time conditions, outperforming traditional methods. The study emphasizes the importance of dynamic signal timing and the integration of advanced algorithms to enhance traffic management strategies.

Author
prajwalp22xhdhhdhd
Language
EN