On a clear day, this works well. However, on a foggy day, the laser light is scattered by water droplets in the air, giving a false impression of the surroundings. This is not ideal for an autonomous car seeking to avoid to obstacles like other vehicles, pedestrians, cyclists, trees, or the edge of the road.
The timings of the fog-distorted blips of reflected radar light follows a
gamma distribution, though. That's quite handy because these distributions are defined by two variables, and thus software connected to the LiDAR can estimate these values on-the-fly to produce a distribution that compensates for the noise caused by the fog. Ultimately, the system has a clearer perception of the surrounding environment by filtering out the effects of the fog using this statistical analysis.
In experiments, Satat set up a metre-long fog chamber, and the system was able to discern the shapes of wooden blocks, a human figurine, and even letters that could not be discerned by the human eye, through the chamber.
“What’s nice about this is that it’s pretty simple,” Satat said. “If you look at the computation and the method, it’s surprisingly not complex. We also don’t need any prior knowledge about the fog and its density, which helps it to work in a wide range of fog conditions.”
