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移动激光扫描在道路车辙深度精确测量中的可行性研究。

Feasibility of Mobile Laser Scanning towards Operational Accurate Road Rut Depth Measurements.

机构信息

Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute FGI, The National Land Survey of Finland, Geodeetinrinne 2, 02430 Masala, Finland.

Department of Built Environment, Aalto University, 02150 Espoo, Finland.

出版信息

Sensors (Basel). 2021 Feb 8;21(4):1180. doi: 10.3390/s21041180.

DOI:10.3390/s21041180
PMID:33567550
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7914922/
Abstract

This paper studied the applicability of the Roamer-R4DW mobile laser scanning (MLS) system for road rut depth measurement. The MLS system was developed by the Finnish Geospatial Research Institute (FGI), and consists of two mobile laser scanners and a Global Navigation Satellite System (GNSS)-inertial measurement unit (IMU) positioning system. In the study, a fully automatic algorithm was developed to calculate and analyze the rut depths, and verified in 64 reference pavement plots (1.0 m × 3.5 m). We showed that terrestrial laser scanning (TLS) data is an adequate reference for MLS-based rutting studies. The MLS-derived rut depths based on 64 plots resulted in 1.4 mm random error, which can be considered adequate precision for operational rutting depth measurements. Such data, also covering the area outside the pavement, would be ideal for multiple road environment applications since the same data can also be used in applications, from high-definition maps to autonomous car navigation and digitalization of street environments over time and in space.

摘要

本文研究了 Roamer-R4DW 移动激光扫描（MLS）系统在道路车辙深度测量中的适用性。该 MLS 系统由芬兰地理空间研究所以及全球导航卫星系统（GNSS）惯性测量单元（IMU）定位系统组成。在研究中，开发了一种全自动算法来计算和分析车辙深度，并在 64 个参考路面图（1.0 m×3.5 m）中进行了验证。结果表明，地面激光扫描（TLS）数据是基于 MLS 的车辙研究的充分参考。基于 64 个图的 MLS 车辙深度产生了 1.4 毫米的随机误差，这可以被认为是操作车辙深度测量的足够精度。由于这些数据还涵盖了路面以外的区域，因此非常适合多种道路环境应用，因为相同的数据也可用于从高清地图到自动驾驶汽车导航以及街道环境随时间和空间的数字化等多种应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4c9/7914922/c28ec3ffc4b3/sensors-21-01180-g017.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4c9/7914922/c28ec3ffc4b3/sensors-21-01180-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4c9/7914922/98d57aa3bd48/sensors-21-01180-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4c9/7914922/48c00acf4b64/sensors-21-01180-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4c9/7914922/bbe9764fb80f/sensors-21-01180-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4c9/7914922/129509001e85/sensors-21-01180-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4c9/7914922/e9000dafa369/sensors-21-01180-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4c9/7914922/5a7481c0e56d/sensors-21-01180-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4c9/7914922/1f678bc1c64b/sensors-21-01180-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4c9/7914922/afa761f69c27/sensors-21-01180-g014.jpg
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