  Using publicly accessible maps, we propose a novel vehicle localization
method that can be applied without using prior light detection and ranging
(LiDAR) maps. Our method generates OSM descriptors by calculating the distances
to buildings from a location in OpenStreetMap at a regular angle, and LiDAR
descriptors by calculating the shortest distances to building points from the
current location at a regular angle. Comparing the OSM descriptors and LiDAR
descriptors yields a highly accurate vehicle localization result. Compared to
methods that use prior LiDAR maps, our method presents two main advantages: (1)
vehicle localization is not limited to only places with previously acquired
LiDAR maps, and (2) our method is comparable to LiDAR map-based methods, and
especially outperforms the other methods with respect to the top one candidate
at KITTI dataset sequence 00.
