Benchmarking Automotive LiDAR Performance in Arctic Conditions

Matti Kutila, Pasi Pyykönen, Maria Jokela, Tobias Gruber, Mario Bijelic, Werner Ritter

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

9 Citations (Scopus)
812 Downloads (Pure)


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.
Original languageEnglish
Title of host publication2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020
PublisherIEEE Institute of Electrical and Electronic Engineers
Number of pages8
ISBN (Electronic)978-1-7281-4149-7
ISBN (Print)978-1-7281-4150-3
Publication statusPublished - 20 Sept 2020
MoE publication typeA4 Article in a conference publication
Event23rd IEEE International Conference on Intelligent Transportation Systems: Virtual - Virtual Conference, Rhodes, Greece
Duration: 20 Sept 202023 Sept 2020
Conference number: 23


Conference23rd IEEE International Conference on Intelligent Transportation Systems
Abbreviated titleITSC 2020


  • sensor
  • LiDAR
  • artic
  • automated
  • passenger car
  • snow


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