강우 시 모바일 LiDAR 성능저하에 대한 실측 점군데이터 기반 해석 연구
Analysis Study of Mobile LiDAR Performance Degradation in Rainfall Based on Real—World Point Cloud Data
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초록
LiDAR는 자율주행차에서 활용되는 핵심적인 센서로서, 3D 정보를 생성할 수 있고 다양한환경요인에 비교적 강건하다는 점에서 활용 범위가 늘어나고 있다. 다만 LiDAR는 원리 상 강우 시 빗방울에 의한 신호감쇠 및 산란현상으로 인해 성능이 일정 부분 저하되는 것으로 알려져 있으며, 이에 LiDAR를 활용한 도로환경 검지 및 활용에 있어 강우에 따른 영향요인 분석이필요하다. 본 연구에서는 강우 시 LiDAR의 성능 저하 요인이라 알려진 신호감쇠 및 산란의영향에 대한 해석을 실측 데이터를 기반하여 진행한다. 강우량 통제가 가능한 실내 실험시설에서 고휘도 재귀반사시트지를 활용한 시설물을 활용하여 데이터를 취득하고, 이를 신호감쇠및 산란의 관점에서 해석하여 강우 시 LiDAR 성능 저하를 정량적으로 확인한다. 점군분포도와 성능지표 분석결과, 비로 인한 신호감쇠와 산란의 영향으로 LiDAR의 성능은 저하된다. 세부적으로 정량 성능지표 분석결과는 LiDAR는 비로 인한 신호감쇠 효과로 주로 Intensity가 감소하며, 신호산란 효과로 NPC와 Intensity가 감소하고, 측정거리 오차가 커졌다.
Abstract
LiDAR is a key sensor used in autonomous vehicles, and its range of applications is expanding because it can generate 3D information and is relatively robust to various environmental factors. However, it is known that LiDAR performance is degraded to some extent due to signal attenuation and scattering by raindrops during rain, and thus the need for analysis of factors affecting rainfall in road environment detection and utilization using LiDAR has been confirmed. In this study, we analyze how signal attenuation and scattering, known as factors degrading LiDAR performance during rain, cause performance degradation based on real data. We acquire data using facilities that utilize high-luminosity retroreflective sheeting in indoor chamber where quantity of rainfall can be controlled, and quantitatively confirm the degradation of LiDAR performance during rain by interpreting it from the perspective of signal attenuation and scattering. According to the point cloud distribution and performance analysis results, LiDAR performance deteriorates due to signal attenuation and scattering caused by rain. Specifically, the quantitative performance analysis shows that LiDAR experiences a decrease in intensity primarily due to signal attenuation from rain, as well as a reduction in NPC and intensity due to signal scattering effects, along with an increase in measurement distance error.
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