VMVG-Loc: Visual Localization for Autonomous Driving using Vector Map and Voxel Grid Map

Abstract

This study proposes a visual localization method using a vector map and voxel grid map with a stereo camera. The two maps provide different modality advantages and are integrated using a particle filter. In contrast to other vector map-based methods, our method does not use road markings because creating and maintaining vector maps that include high-accuracy road markings is laborious. Furthermore, it limits the regions where they are available. This method uses only lane center-lines from vector maps, which are easier to create than road markings. The method performs ray casting and computes the reprojection error to evaluate the vehicle position for voxel grid maps. Although this makes the method environmentally sensitive, the constraints by lanes make the estimation stable. Experiments confirmed that the method could perform localization stably and accurately without failure even over long distances. In addition, an ablation study showed the benefits of combining both maps.