Adaptive Traffic signal control strategy based on traffic flow sensing

This paper presents an adaptive traffic signal control strategy based on real-time traffic flow monitoring. Urban traffic congestion has become a critical issue, which not only leads to travelling time delays and driving stress, but also increases fuel consumption and air pollution. Existing traffic management systems are usually fixed and cannot adapt to the instantaneous traffic flow changes. Our system uses CCTV cameras to monitor the number of vehicles at each intersection in real time, and classifies and identifies the vehicles by target detection techniques such as YOLO. According to the density of traffic flow in each direction, the green light duration of each traffic signal is dynamically adjusted to achieve adaptive control. This strategy based on real-time traffic flow sensing can effectively optimise the green time, reduce unnecessary delays and congestion, and thus reduce fuel consumption and pollution emissions. Compared with the traditional fixed signal control scheme, our proposed adaptive system can better adapt to the complex and changing urban traffic conditions, and provide a new solution for more efficient and environmentally friendly traffic management.