Localization in digital maps for road course estimation using grid maps

Abstract

Grid maps are a reliable representation of the environment. Based on a generic grid map definition, this paper presents three formulations: a laser scanner based occupancy grid, a video grid based on the Inverse Perspective Mapping and a novel feature grid, where lane marking features are used. Furthermore, this contribution presents a road course estimation based on such grid maps which yields estimations above 120m. Therefore, a digital road map (comparable to maps of GPS navigation systems) is matched to a grid map. Thus, a global position in the road map is estimated. Finally, a novel evaluation approach is presented to quantize the results of this grid map based map match.