An automated process of generating traffic sign HD maps for autonomous vehicles. Tailored the PointNet neural network model to enhance traffic sign segmentation, resulting in 83% average recall rate. Adjusted GoogLeNet model to attain an accuracy rate over 90% in classifying traffic signs. The proposed process provides a more efficient approach to extracting information from mobile mapping systems.