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One of the hardest challenges to face in the development of a non GPS-basedlocalization system for autonomous vehicles is the changes of the environment.LiDAR-based systems typically try to match the last measurements obtained witha previously recorded map of the area. If the existing map is not updated alongtime, there is a good chance that the measures will not match the environmentwell enough, causing the vehicle to lose track of its location. In this paper,we present and analyze experimental results regarding the robustness andprecision of a map-matching based localization system over a certain period oftime in the following three cases: (1) without any update of the initial map,(2) updating the map as the vehicle moves and (3) with map updates that takeinto account surrounding structures labeled as "fixed" which are treateddifferently. The environment of the tests is a busy parking area, which ensuresdrastic changes from one day to the next. The precision is obtained bycomparing the positions computed using the map with the ones provided by aReal-Time Kinematic GPS system. The experimental results reveal a positioningerror of about 6cm which remains stable even after 23 days when using fixedstructures on the working area.

An Experimental Evaluation of Robustness and Precision for Long-term LiDAR-based Localization in Highly Changing Environments