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A driving behavior identification method of YOLOV5s detection network with integrated channel attention mechanism is designed to detect and identify the driver"s driving behavior in the cab in real time, so as to correct the driver"s bad driving behavior and reduce the probability of traffic accidents. The image data set of the hand movements of the driver in the cab is established, the channel attention mechanism is introduced into the YOLOv5s network structure, the effect of configuration quantity and the improved YOLOV5s with channel attention can retain the features of large information and suppress irrelevant features, and reduce the number and complexity of model parameters to accelerate the detection speed. The test results show that compared with the original YOLOV5s network, the improved YOLOV5s is comparable in average accuracy and recall rate, while the detection speed is increased by 26.08%. This method can better meet the real-time monitoring requirements of drivers" hand movements.