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A Methodology to Model the Rain and Fog Effect on the Performance of Automotive LiDAR Sensors

  • In this work, we introduce a novel approach to model the rain and fog effect on the light detection and ranging (LiDAR) sensor performance for the simulation-based testing of LiDAR systems. The proposed methodology allows for the simulation of the rain and fog effect using the rigorous applications of the Mie scattering theory on the time domain for transient and point cloud levels for spatial analyses. The time domain analysis permits us to benchmark the virtual LiDAR signal attenuation and signal-to-noise ratio (SNR) caused by rain and fog droplets. In addition, the detection rate (DR), false detection rate (FDR), and distance error derror of the virtual LiDAR sensor due to rain and fog droplets are evaluated on the point cloud level. The mean absolute percentage error (MAPE) is used to quantify the simulation and real measurement results on the time domain and point cloud levels for the rain and fog droplets. The results of the simulation and real measurements match well on the time domain and point cloud levels if the simulatedIn this work, we introduce a novel approach to model the rain and fog effect on the light detection and ranging (LiDAR) sensor performance for the simulation-based testing of LiDAR systems. The proposed methodology allows for the simulation of the rain and fog effect using the rigorous applications of the Mie scattering theory on the time domain for transient and point cloud levels for spatial analyses. The time domain analysis permits us to benchmark the virtual LiDAR signal attenuation and signal-to-noise ratio (SNR) caused by rain and fog droplets. In addition, the detection rate (DR), false detection rate (FDR), and distance error derror of the virtual LiDAR sensor due to rain and fog droplets are evaluated on the point cloud level. The mean absolute percentage error (MAPE) is used to quantify the simulation and real measurement results on the time domain and point cloud levels for the rain and fog droplets. The results of the simulation and real measurements match well on the time domain and point cloud levels if the simulated and real rain distributions are the same. The real and virtual LiDAR sensor performance degrades more under the influence of fog droplets than in rain.show moreshow less

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Metadaten
Author:Arsalan HaiderORCiD, Marcell Pigniczki, Shotokaro Koyama, Michael H. Köhler, Lukas HaasORCiDGND, Maximilian Fink, Michael Schardt, Koji Nagase, Thomas ZehORCiDGND, Abdulkadir Eryildirim, Tim PoguntkeGND, Hideo Inoue, Martin Jakobi, Alexander W. Koch
DOI:https://doi.org/10.3390/s23156891
Identifier:1424-8220 OPAC HS OPAC extern
Parent Title (English):Sensors
Publisher:MDPI
Place of publication:Basel
Document Type:Article
Language:English
Date of Publication (online):2023/08/03
Year of first Publication:2023
Tag:LiDAR sensor; rain; fog; sunlight; advanced driver-assistance system; backscattering; Mie theory; open simulation interface; functional mock-up interface; functional mock-up unit
Volume:23
Issue:15
Article Number:6891
Number of pages:25 Seiten
Institutes:IFM - Institut für Fahrerassistenz und vernetzte Mobilität
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften
Open Access:open_access
Research focus:FSP2: Mobilität
Publication Lists:Poguntke, Tim
Zeh, Thomas
Haider, Arsalan
Pigniczki, Marcell
Haas, Lukas
Publication reviewed:begutachtet
Licence (German):Creative Commons - CC BY - Namensnennung 4.0 International
Release Date:2023/09/13
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