Automatic Extraction of Traffic Signs and Lights From Mobile Mapping Datasets For HD Maps Generation

Abstract

In recent years the rise of the autonomous vehicles (AVs) industry leads many scholars into the field of high definition (HD) maps and HD maps is a basic but important component for autonomous driving However the procedure of generating the HD maps is manual now and that costs a lot of time and labor thus that hinder the development of AVs industry Therefore this research proposed an algorithm for generating HD maps automatically Base on the issue above in this research two classes of targets traffic sign and traffic light were chosen for testing the algorithm The procedure of the proposed algorithm in this research was divided into four parts The first was the pre-processing for point cloud data such as the noise height or intensity filter This step improved the efficiency and accuracy of overall research The second was the image classification by the AI model the information of HD maps can be divided into geometry and attribute information The image classification provided the precise attribute information compared with the point cloud data The third was the linking of point cloud and image data the correct attribute and geometry information were combined according to the voting mechanism The final was the calculation for the needed information in HD maps According to the proposed method in this study the accuracy of the result was higher than the regulation in the Taiwan HD maps standard which is 30 centimeters for three- dimensional accuracy and the accuracy for the attribute and count can reach 99 9 percent This research stated that the method of generating the HD maps automatically is feasible and accurate which can assist the development of AVs industry

Date of Award	2020
Original language	English
Supervisor	Yi-Hsing Tseng (Supervisor)