Benchmarking Image Sensors Under Adverse Weather Conditions for Autonomous Driving

written by: Mario Bijelic¹, Tobias Gruber¹ and Werner Ritter

¹Mario Bijelic and Tobias Gruber have contributed equally to the work.

Adverse weather conditions are very challenging for autonomous driving because most of the state-of-the-art sensors stop working reliably under these conditions. In order to develop robust sensors and algorithms, tests with current sensors in defined weather conditions are crucial for determining the impact of bad weather for each sensor. This work describes a testing and evaluation methodology that helps to benchmark novel sensor technologies and compare them to state-of-the-art sensors. As an example, gated imaging is compared to standard imaging under foggy conditions. It is shown that gated imaging outperforms state-of-the-art standard passive imaging due to time-synchronized active illumination.

The paper was published @ The 2018 29^th IEEE Intelligent Vehicles Symposium.
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Or visit the preprint at ArXiv Link.