Perception Sensors in Adverse Weather

Simulation-based testing supports the challenging task of safety validation of automated driving functions. Virtual testing always entails modeling of automotive perception sensors. In the real world, these sensors are exposed to adverse influences by environmental conditions like rain, fog, snow etc. Therefore, such influences need to be reflected in the simulation models, but prior to modeling, they need to be systematically assessed in the real world. This data set consists of measurements in a static test setup over the course of 6 months in fall, winter and spring containing weather conditions like rain, snow, fog and direct sun light in different intensities.

The dataset including further meta data is available for free from TUdatalib.