Performance of Mobile LiDAR in Real Road Driving Conditions

The performance of LiDAR sensors deteriorates under adverse weather conditions such as rainfall. However, few studies have empirically analyzed this phenomenon. Hence, we investigated differences in sensor data due to environmental changes (distance from objects (road signs), object material, vehicl...

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Auteurs principaux:	Jisoo Kim, Bum-jin Park, Chang-gyun Roh, Youngmin Kim
Format:	article
Langue:	EN
Publié:	MDPI AG 2021
Sujets:	automated vehicle LiDAR real road performance empirical test point cloud Chemical technology TP1-1185
Accès en ligne:	https://doaj.org/article/e2d87250ac3e48d5b3f1eaa8361215ac
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id	oai:doaj.org-article:e2d87250ac3e48d5b3f1eaa8361215ac
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spelling	oai:doaj.org-article:e2d87250ac3e48d5b3f1eaa8361215ac2021-11-25T18:56:38ZPerformance of Mobile LiDAR in Real Road Driving Conditions10.3390/s212274611424-8220https://doaj.org/article/e2d87250ac3e48d5b3f1eaa8361215ac2021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7461https://doaj.org/toc/1424-8220The performance of LiDAR sensors deteriorates under adverse weather conditions such as rainfall. However, few studies have empirically analyzed this phenomenon. Hence, we investigated differences in sensor data due to environmental changes (distance from objects (road signs), object material, vehicle (sensor) speed, and amount of rainfall) during LiDAR sensing of road facilities. The indicators used to verify the performance of LiDAR were numbers of point cloud (NPC) and intensity. Differences in the indicators were tested through a two-way ANOVA. First, both NPC and intensity increased with decreasing distance. Second, despite some exceptions, changes in speed did not affect the indicators. Third, the values of NPC do not differ depending on the materials and the intensity of each material followed the order aluminum > steel > plastic > wood, although exceptions were found. Fourth, with an increase in rainfall, both indicators decreased for all materials; specifically, under rainfall of 40 mm/h or more, a substantial reduction was observed. These results demonstrate that LiDAR must overcome the challenges posed by inclement weather to be applicable in the production of road facilities that improve the effectiveness of autonomous driving sensors.Jisoo KimBum-jin ParkChang-gyun RohYoungmin KimMDPI AGarticleautomated vehicleLiDARreal roadperformanceempirical testpoint cloudChemical technologyTP1-1185ENSensors, Vol 21, Iss 7461, p 7461 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	automated vehicle LiDAR real road performance empirical test point cloud Chemical technology TP1-1185
spellingShingle	automated vehicle LiDAR real road performance empirical test point cloud Chemical technology TP1-1185 Jisoo Kim Bum-jin Park Chang-gyun Roh Youngmin Kim Performance of Mobile LiDAR in Real Road Driving Conditions
description	The performance of LiDAR sensors deteriorates under adverse weather conditions such as rainfall. However, few studies have empirically analyzed this phenomenon. Hence, we investigated differences in sensor data due to environmental changes (distance from objects (road signs), object material, vehicle (sensor) speed, and amount of rainfall) during LiDAR sensing of road facilities. The indicators used to verify the performance of LiDAR were numbers of point cloud (NPC) and intensity. Differences in the indicators were tested through a two-way ANOVA. First, both NPC and intensity increased with decreasing distance. Second, despite some exceptions, changes in speed did not affect the indicators. Third, the values of NPC do not differ depending on the materials and the intensity of each material followed the order aluminum > steel > plastic > wood, although exceptions were found. Fourth, with an increase in rainfall, both indicators decreased for all materials; specifically, under rainfall of 40 mm/h or more, a substantial reduction was observed. These results demonstrate that LiDAR must overcome the challenges posed by inclement weather to be applicable in the production of road facilities that improve the effectiveness of autonomous driving sensors.
format	article
author	Jisoo Kim Bum-jin Park Chang-gyun Roh Youngmin Kim
author_facet	Jisoo Kim Bum-jin Park Chang-gyun Roh Youngmin Kim
author_sort	Jisoo Kim
title	Performance of Mobile LiDAR in Real Road Driving Conditions
title_short	Performance of Mobile LiDAR in Real Road Driving Conditions
title_full	Performance of Mobile LiDAR in Real Road Driving Conditions
title_fullStr	Performance of Mobile LiDAR in Real Road Driving Conditions
title_full_unstemmed	Performance of Mobile LiDAR in Real Road Driving Conditions
title_sort	performance of mobile lidar in real road driving conditions
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/e2d87250ac3e48d5b3f1eaa8361215ac
work_keys_str_mv	AT jisookim performanceofmobilelidarinrealroaddrivingconditions AT bumjinpark performanceofmobilelidarinrealroaddrivingconditions AT changgyunroh performanceofmobilelidarinrealroaddrivingconditions AT youngminkim performanceofmobilelidarinrealroaddrivingconditions
_version_	1718410559541477376

Performance of Mobile LiDAR in Real Road Driving Conditions

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