SMART CONTROL OF TRAFFIC LIGHTS
Keywords:
Traffic congestion, Urban mobility, Image processing, Traffic density, Artificial intelligence, Signal optimization, Real-time monitoring, Smart traffic management, Traffic flow Megacities.Abstract
Traffic congestion is increasingly becoming a critical issue in urban areas due to the rapid growth of
population and automobiles. This problem, particularly pronounced in megacities, leads to significant delays,
stress for drivers, and increased fuel consumption and air pollution. The growing nature of traffic congestion
makes it imperative to calculate real-time road traffic density for optimized signal control and more effective
traffic management. The efficiency of the traffic controller plays a pivotal role in ensuring smooth traffic flow,
thus highlighting the need for innovative solutions to accommodate this growing demand. Our proposed system
leverages live images from traffic cameras to calculate traffic density using image processing techniques and
artificial intelligence (AI) algorithms, which can help optimize traffic signal management and improve overall
traffic control systems [1][2][5][6][7]. This system integrates advanced technologies such as intelligent traffic
systems, image processing, and AI for real-time monitoring and management of traffic flow
