  Range-measuring sensors play a critical role in autonomous driving systems.
While LiDAR technology has been dominant, its vulnerability to adverse weather
conditions is well-documented. This paper focuses on secondary adverse
conditions and the implications of ill-reflective surfaces on range measurement
sensors. We assess the influence of this condition on the three primary ranging
modalities used in autonomous mobile robotics: LiDAR, RADAR, and Depth-Camera.
Based on accurate experimental evaluation the papers findings reveal that under
ill-reflectivity, LiDAR ranging performance drops significantly to 33% of its
nominal operating conditions, whereas RADAR and Depth-Cameras maintain up to
100% of their nominal distance ranging capabilities. Additionally, we
demonstrate on a 1:10 scaled autonomous racecar how ill-reflectivity adversely
impacts downstream robotics tasks, highlighting the necessity for robust range
sensing in autonomous driving.
