In view of the high time cost of traditional convolutional neural network, an improved convolutional neural network is designed, which has a reduction in the number of the convolutional kernels and an increase of the pooling methods. To solve the road traffic sign recognition problem of autopilot system and auxiliary driving system in the real scenario, the improved convolutional neural network is applied to road traffic sign recognition for the purpose of identifying traffic sign in a relatively short period of time. Taking the graphic data set GTRSB, real traffic sign image data as a sample, the real traffic sign is identified, and the overall recognition accuracy reaches 98.38%. Experimental results show that this method can reduce the recognition time while maintaining high recognition accuracy.