  One of the hardest challenges to face in the development of a non GPS-based
localization system for autonomous vehicles is the changes of the environment.
LiDAR-based systems typically try to match the last measurements obtained with
a previously recorded map of the area. If the existing map is not updated along
time, there is a good chance that the measures will not match the environment
well enough, causing the vehicle to lose track of its location. In this paper,
we present and analyze experimental results regarding the robustness and
precision of a map-matching based localization system over a certain period of
time 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 take
into account surrounding structures labeled as "fixed" which are treated
differently. The environment of the tests is a busy parking area, which ensures
drastic changes from one day to the next. The precision is obtained by
comparing the positions computed using the map with the ones provided by a
Real-Time Kinematic GPS system. The experimental results reveal a positioning
error of about 6cm which remains stable even after 23 days when using fixed
structures on the working area.
