Automated Modeling of Road Networks for High-Definition Maps in OpenDRIVE Format Using Mobile Mapping Measurements

Abstract

With growing attention being devoted to autonomous vehicle (AV) safety, people have recently attached importance to high-definition (HD) maps. HD maps are not limited by environmental factors and can limit AVs driving in certain lanes. HD maps provide accurate auxiliary information on factors such as road geometry, traffic sign placement, and traffic topology. Nowadays, most HD maps are made from point clouds data, and this data contains accurate 3D position information. However, the production costs associated with HD maps are substantial. This article proposes an algorithm that reduces a great amount of time and human resource. The algorithm is divided into three phases, lane lines’ extraction from point clouds, modelling lane lines with attributes, and building OpenDRIVE file. The algorithm extracts lane lines resting on intensity value within the range of roads. Next, it models lane lines by cubic spline interpolation with the result of first phase, and build the OpenDRIVE file following the announcement of OpenDRIVE. The final result is compared with the verified HD map from the mapping company to analyze the accuracy. The root mean square (RMSE) obtained were 0.069 and 0.079 m for 2D and 3D maps, respectively.

Automatic Odometry-Less OpenDRIVE Generation From Sparse Point Clouds

“…An automated approach exporting OpenDRIVE is presented in [14], using the trajectory of the ego vehicle and a ground-facing laser scanner. A multistage reconstruction process is used to recreate the road network based on extracted road edges, line marking classification, and the trajectory.…”

“…In [14], the authors extensively compare different formats for HD map creation, e.g., Autoware Vector Map, Open-DRIVE, Lanelet2, and Navigation Data Standard. Based on their evaluation and our focus on automotive simulation, OpenDRIVE is selected as HD map format.…”

“…Based on their evaluation and our focus on automotive simulation, OpenDRIVE is selected as HD map format. One of the main reasons is the wide adoption in the automotive industry and support by tools and software platforms for creating, editing, and using road data in simulation and testing scenarios [14]. OpenDRIVE originates from the automotive industry's efforts for standardization and provides a comprehensive and flexible framework for describing the geometry, topology, and attributes of roads [20].…”

“…Through the nature of point clouds, methods like nearest neighbor would yield wrong connections between lanes. Hence, for the construction of the lanes, related research, e.g., [14], [15], integrates ego trajectory information to solve this limitation, which in return requires an accurate GNSS and/or IMU setup.…”

On the Estimation of Vehicle Trajectories With a Mini-Uas

“…• providing, in addition to the user trajectories, high resolution geometric information of the test area (e.g. HD maps (Chiang et al, 2022)) and of the involved vehicles;…”