A Benchmark for Lidar Sensors in Fog: Is Detection Breaking Down?
This addresses the critical issue of lidar reliability in adverse weather for autonomous driving, but it is incremental as it focuses on parameter tuning rather than a new method.
The paper tested four state-of-the-art lidar sensors in foggy conditions to identify problems and disturbance patterns, and investigated how tuning internal parameters can improve their performance, with results showing specific improvements but no concrete numbers provided.
Autonomous driving at level five does not only means self-driving in the sunshine. Adverse weather is especially critical because fog, rain, and snow degrade the perception of the environment. In this work, current state of the art light detection and ranging (lidar) sensors are tested in controlled conditions in a fog chamber. We present current problems and disturbance patterns for four different state of the art lidar systems. Moreover, we investigate how tuning internal parameters can improve their performance in bad weather situations. This is of great importance because most state of the art detection algorithms are based on undisturbed lidar data.