Testing and Predicting the Impact of Adverse Weather on LiDAR Performance in ADAS

Severe weather, especially rain and fog, affects LiDAR performance, which in turn impacts the functional safety of onboard ADAS. Understanding and predicting the mechanisms of weather effects on LiDAR is an urgent issue. In ADAS, the AEB module is particularly sensitive to LiDAR performance. This paper analyzes the impact of rain, fog, and other weather conditions on the AEB system through extensive real-world experiments, and proposes a data-driven LiDAR-weather impact prediction model to forecast changes in LiDAR's key performance metrics under different weather conditions. The results show that the model has minimal prediction error and aligns well with experimental findings.