Benchmarking Automotive LiDAR Performance in Arctic Conditions

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

doi:10.1109/ITSC45102.2020.9294367

Benchmarking Automotive LiDAR Performance in Arctic Conditions

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

Mercedes-Benz AG

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

13 Citations (Scopus)

970 Downloads (Pure)

Abstract

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 language	English
Title of host publication	2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020
Publisher	IEEE Institute of Electrical and Electronic Engineers
Number of pages	8
ISBN (Electronic)	978-1-7281-4149-7
ISBN (Print)	978-1-7281-4150-3
DOIs	https://doi.org/10.1109/ITSC45102.2020.9294367
Publication status	Published - 20 Sept 2020
MoE publication type	A4 Article in a conference publication
Event	23rd IEEE International Conference on Intelligent Transportation Systems: Virtual - Virtual Conference, Rhodes, Greece Duration: 20 Sept 2020 → 23 Sept 2020 Conference number: 23

Conference

Conference	23rd IEEE International Conference on Intelligent Transportation Systems
Abbreviated title	ITSC 2020
Country/Territory	Greece
City	Rhodes
Period	20/09/20 → 23/09/20

Keywords

sensor
LiDAR
artic
automated
passenger car
snow

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10.1109/ITSC45102.2020.9294367

Kutila_Paper_35_IEEE_ITSC_2020_LiDAR_artic_weather_20092020Submitted manuscript, 2.33 MB

Cite this

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title = "Benchmarking Automotive LiDAR Performance in Arctic Conditions",

abstract = "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.",

keywords = "sensor, LiDAR, artic, automated, passenger car, snow",

author = "Matti Kutila and Pasi Pyyk{\"o}nen and Maria Jokela and Tobias Gruber and Mario Bijelic and Werner Ritter",

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doi = "10.1109/ITSC45102.2020.9294367",

language = "English",

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booktitle = "2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

address = "United States",

note = "23rd IEEE International Conference on Intelligent Transportation Systems : Virtual, ITSC 2020 ; Conference date: 20-09-2020 Through 23-09-2020",

}

Kutila, M , Pyykönen, P , Jokela, M, Gruber, T, Bijelic, M & Ritter, W 2020, Benchmarking Automotive LiDAR Performance in Arctic Conditions. in 2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020., 9294367, IEEE Institute of Electrical and Electronic Engineers, 23rd IEEE International Conference on Intelligent Transportation Systems, Rhodes, Greece, 20/09/20. https://doi.org/10.1109/ITSC45102.2020.9294367

Benchmarking Automotive LiDAR Performance in Arctic Conditions. / Kutila, Matti ; Pyykönen, Pasi ; Jokela, Maria et al.
2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020. IEEE Institute of Electrical and Electronic Engineers, 2020. 9294367.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Benchmarking Automotive LiDAR Performance in Arctic Conditions

AU - Kutila, Matti

AU - Pyykönen, Pasi

AU - Jokela, Maria

AU - Gruber, Tobias

AU - Bijelic, Mario

AU - Ritter, Werner

N1 - Conference code: 23

PY - 2020/9/20

Y1 - 2020/9/20

N2 - 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.

AB - 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.

KW - sensor

KW - LiDAR

KW - artic

KW - automated

KW - passenger car

KW - snow

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M3 - Conference article in proceedings

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PB - IEEE Institute of Electrical and Electronic Engineers

T2 - 23rd IEEE International Conference on Intelligent Transportation Systems

Y2 - 20 September 2020 through 23 September 2020

ER -

Benchmarking Automotive LiDAR Performance in Arctic Conditions

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Keywords

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