Aiming at the limitation of face detection accuracy degradation when facing light changes or complex background in driver fatigue detection methods, an improved MTCNN network is proposed. By optimising the MTCNN network, the coordinate attention mechanism and batch normalisation algorithm are introduced in all three sub-networks to improve the model′s localisation accuracy of the driver′s face, enhance the convergence speed and stability of the network, and enhance the suppression of overfitting. The experimental results show that the accuracy of the improved MTCNN model on the fatigue driving dataset reaches 98.78%, which is 2.43% higher than that of the original model, and the number of parameters of the model is only 0.5 M, which has good face detection accuracy and deployability. In addition, combining the improved MTCNN model with the PFLD model, a reasonable fatigue parameter threshold is set based on the experiments, and a more accurate fatigue driving detection is achieved.