Testing and Validation of Automotive Point-Cloud Sensors in Adverse Weather Conditions
VTT Technical Research Centre of Finland, P.O. Box 1300, FI-33101 Tampere, Finland
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Appl. Sci. 2019, 9(11), 2341; https://doi.org/10.3390/app9112341
Received: 29 March 2019 / Revised: 31 May 2019 / Accepted: 4 June 2019 / Published: 7 June 2019
(This article belongs to the Special Issue LiDAR and Time-of-flight Imaging)
Light detection and ranging sensors (LiDARS) are the most promising devices for range sensing in automated cars and therefore, have been under intensive development for the last five years. Even though various types of resolutions and scanning principles have been proposed, adverse weather conditions are still challenging for optical sensing principles. This paper investigates proposed methods in the literature and adopts a common validation method to perform both indoor and outdoor tests to examine how fog and snow affect performances of different LiDARs. As suspected, the performance degraded with all tested sensors, but their behavior was not identical.
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Keywords:
LiDAR; adverse weather; automatic driving
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MDPI and ACS Style
Jokela, M.; Kutila, M.; Pyykönen, P. Testing and Validation of Automotive Point-Cloud Sensors in Adverse Weather Conditions. Appl. Sci. 2019, 9, 2341.
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