Adaptive Traffic Control System with Emergency Vehicle Detection

Urban traffic congestion gets resolved through the implementation of the Adaptive Traffic Control System with Emergency Vehicle Detection which provides a modern approach to traffic management. The system applies machine learning alongside image processing methods to determine traffic density while YOLO or SSD object detectors help detect and count vehicles. Varied traffic light timer settings depend on the observed traffic density which reduces waiting times and optimizes transport efficiency. This traffic management system combines emergency vehicle detection functions which expedite the clearing of traffic lanes when emergency response vehicles require passage. The system's methodology functions using basic hardware components that enable its wide deployment at costefficient prices. A system implementation minimizes emergency response delays as well as decreasing waiting periods for all vehicles while improving both safety and operational efficiency. Development work should focus on including Vehicle-toInfrastructure communication systems and complex traffic situation analysis approaches.