Existing inflexible and ineffective traffic light control at a key intersection can often lead to congestion due the complexity of dynamics, how find optimal timing strategy is significant challenge. This paper proposes optimization method based on double dueling deep Q-network, MaxPressure, Self-organizing lights (SOTL), namely EP-D3QN, which controls flows by dynamically adjusting duration in...

Our research is the design of a traffic signal violation detection system using machine learning that learns to prevent increasing number road accidents. The optimized in terms accuracy by region interest and location vehicle with red-signal state. By modifying some parameters YOLOV5s re-training COCO dataset, we can create model which be predicted high 82% for identification, 90% status change...