Concerning the inaccurate vehicle information captured by the license plate of the existing intelligent traffic system, a vehicle logo recognition method based on the Convolutional Neural Network (CNN) combined with different layer features, namely Multi-CNN, was proposed. Firstly, the different layer features were obtained using CNN. Secondly, the extracted features were joined together and regarded as the input of the fully connected layer to get classifiers. The theoretical analysis and simulation results show that, compared with the traditional method, Multi-CNN method can reduce the training time and increase the recognition accuracy to 98.7%.