The invention discloses a pedestrian identification method under a road traffic environment based on improved YOLOv3. The method comprises the following steps of: S1, acquiring and pre-processing an image, and making a pedestrian sample set; 2, calculating the length-width ratio of the pedestrian candidate frames by using a clustering algorithm and the training set; 3, inputting the training set into the YOLOv3 network for multi-task training and saving the trained weight file; S4, inputting a picture to be recognized into the YOLOv3 network to obtain a multi-scale characteristic map; S5, using a logistic function to activate the x, y, confidence degree and category probability of the network prediction, and obtaining the coordinates, confidence degree and category probability of all prediction frames by judging the threshold value; S6, generating a final target detection frame and a recognition result by carrying out the non-maximum value suppression processing on the above result. The method of the invention solves the problem of low detection accuracy of the prior method, realizes the multi-task training, does not need additional storage space, and is high in detection accuracyand fast in speed.