AUTOMATED MODELLING OF ROAD FOR HIGH-DEFINITION MAPS WITH OPENDRIVE FORMAT UTILIZING MOBILE MAPPING MEASUREMENTS
Keywords: OpenDRIVE, Extraction of Road Factors, Lane Lines, Point Cloud, Automated Modelling, HD Maps
Abstract. High-definition maps (HD Maps) becomes a trend supporting autonomous vehicles (AVs) which provides accurate auxiliary information about geometries of road, such as center lines of lanes, geometries of roads, traffic signs, etc. It is not restricted by the severe environment, lack of Global Navigation Satellite System (GNSS) signal, or torrential rain, for Avs; furthermore, the standard of HD Maps is defined as tens of centimeters positioning level. However, the production cost of HD Maps is enormous involving human resources and time. The general way of producing HD Maps is to vectorize the roads from point clouds to shapefiles and import them into Geographic Information System (GIS) software to generate HD Maps. In order to simplify this complicated process, this article purposes an algorithm to automated generate high-definition maps from road marks’ data which is extracted from point clouds. The methodology in this article is mainly dived into three steps, extraction of road marks, classify lane lines, and modelling OpenDRIVE files. The achieved 2D and 3D accuracies of proposed algorithm in first fields are about 0.069 m in 2D and 0.107 m, respectively.