Projecting Lane Lines from Proxy High-Definition Maps for Automated Vehicle Perception in Road Occlusion Scenarios 2023-01-0051

Contemporary ADS and ADAS localization technology utilizes real-time perception sensors such as visible light cameras, radar sensors, and lidar sensors, greatly improving transportation safety in sufficiently clear environmental conditions. However, when lane lines are completely occluded, the reliability of on-board automated perception systems breaks down, and vehicle control must be returned to the human driver. This limits the operational design domain of automated vehicles significantly, as occlusion can be caused by shadows, leaves, or snow, which all occur in many regions. High-definition map data, which contains a high level of detail about road features, is an alternative source of the required lane line information. This study details a novel method where high-definition map data are processed to locate fully occluded lane lines, allowing for automated path planning in scenarios where it would otherwise be impossible. A proxy high-definition map dataset with high-accuracy lane line geospatial positions was generated for routes at both the Eaton Proving Grounds and Campus Drive at Western Michigan University (WMU). Once map data was collected for both routes, the WMU Energy Efficient and Autonomous Vehicles Laboratory research vehicles were used to collect video and high-accuracy GNSS data. The map data and GNSS data were fused together using a sequence of data processing and transformation techniques to provide occluded lane line geometry from the perspective of the ego vehicle camera system. The recovered geometry is then overlaid on the video feed to provide lane lines, even when they are completely occluded and invisible to the camera. This enables the control system to utilize the projected lane lines for path planning, rather than failing due to undetected, occluded lane lines. This initial study shows that utilization of technology outside of the norms of automated vehicle perception successfully expands the operational design domain to include occluded lane lines, a necessary and critical step for the achievement of complete vehicle autonomy.