Benchmarking Automotive LiDAR Performance in Arctic Conditions

• Published in: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)
• Main Authors: Kutila, Matti, Pyykönen, Pasi, Jokela, Maria, Gruber, Tobias, Bijelic, Mario, Ritter, Werner
• Format: Article in Journal/Newspaper
• Language: English
• Published: IEEE Institute of Electrical and Electronic Engineers 2020
• Subjects: sensor; LiDAR; artic; automated; passenger car; snow; Arctic
• Online Access: https://cris.vtt.fi/en/publications/bf70b6a9-3ea1-4a37-b69e-785d0cc0e532; https://doi.org/10.1109/ITSC45102.2020.9294367; https://cris.vtt.fi/ws/files/35400640/Kutila_Paper_35_IEEE_ITSC_2020_LiDAR_artic_weather_20092020.pdf; http://www.scopus.com/inward/record.url?scp=85099649867&partnerID=8YFLogxK

This work shows and analyzes the LiDAR performance in real-world heavy winter conditions captured in Northern Europe. We review how low temperatures, saltedroads and turbulent snow in front of a passenger car influence LiDAR systems developed for automated driving functions. Two test cars were driven in the north of Finland and Sweden for 1.5 weeks to gather a large amount of point cloud data in different urban and rural scenarios. We show that the benchmarked LiDAR sensors have surprising performance differences in winter. Some of the sensors got mechanically frozen whereas others went out of the measurement range and were completely blind. Especially the latest multi-layer sensors showed significant problems. We propose countermeasures such as heating and protecting in order to improve the performance and suggest how the software can take the performance degradation into account.