Testing and Validation of Automotive Point-Cloud Sensors in Adverse Weather Conditions

Abstract

Light detection and ranging sensors (LiDARS) are the most promising devices for range sensing in automated cars and therefore, have been under intensive development for the last five years. Even though various types of resolutions and scanning principles have been proposed, adverse weather conditions are still challenging for optical sensing principles. This paper investigates proposed methods in the literature and adopts a common validation method to perform both indoor and outdoor tests to examine how fog and snow affect performances of different LiDARs. As suspected, the performance degraded with all tested sensors, but their behavior was not identical.

Reshaping Field of View and Resolution with Segmented Reflectors: Bridging the Gap between Rotating and Solid-State LiDARs

“…Another example of small obstacles that create occlusion is snow. In adverse weather conditions, as described by [14], it is assumed likely that a LiDAR combined with the reflector can perform significantly better than the LiDAR alone. No experiments have yet been conducted to validate this, but the expectation arises from the principle of redundant measurements.…”

“…In addition to the possible loss of data from occlusion, it is well documented by [14] that traditional rotating LiDARs have severely reduced performance in adverse weather conditions such as dense fog, rain and turbulent snow. The authors discovered, in a turbulent snow driving experiment, that all tested sensors were blocked by the powder snow and their viewing distance was shortened.…”

A Review and Perspective on Optical Phased Array for Automotive LiDAR

“…For this reason, RADAR is reasonably accurate to measure target range and speed components in the radial direction, while accuracy is lower on the lateral direction (with uncertainties that can be in excess of 1 m). RADAR is robust to luminosity and to adverse weather: the performance is hardly affected by medium-light rain, fog, and even snow [45]. Cost is around one thousand dollars, and covered region can vary from short range (50-100m and 120 o HFoV) up to long range (>250m and ~10 o HFoV), but usually VFoV is very limited, and RADAR is not suitable to measure elevation [46].…”

An Overview of Lidar Imaging Systems for Autonomous Vehicles

“…These so-called spinning lidars increase data and frame rate while enabling for each detector a narrow field of view, which makes them very efficient energetically and, thus, able to reach long distances. A comparable approach has also been developed for flash lidars with an array of detectors and multiple beams mounted on a rotating axis [85]. These spinning approaches obviously demand line-shaped illumination of the scene.…”

“…However, the quality of the detection under fog, rain and snow, especially if they are extreme, becomes severely degraded, especially regarding range [142] due to the absorption and scattering events induced by water droplets. This introduces a large number of false detection alarms from the backscattered intensity, reducing the reliability of the sensor [85,143]. Further, snowflakes, fog and rain droplets have different shapes, distributions and sizes and affect different aspects of the detection, complicating a precise modeling [144].…”