Front-of-vehicle road extraction method based on feature fusion difference of vehicle LiDAR

doi:10.13474/j.cnki.11-2246.2023.0352

Abstract

Abstract: In order to cope with the changing road environment during driving and divide the drivable area of the current road in front of the vehicle, this paper proposes a detection method for the road in front of the vehicle based on multi-feature fusion difference. This algorithm extracts the ground point cloud from the original point cloud by morphological filtering method, statistically summarizes the ground point cloud data to define the operation domain, divides the differential element size and starting point of different depths in the operation domain, fuses the characteristic parameters in the differential element, forms a feature matrix, solves the differential matrix, and performs threshold filtering, so as to realize the extraction of the point cloud in front of the vehicle. In this paper the extraction algorithm of the relevant road point cloud is compared to,which highlight its excellent performance and then the road extraction effect of different depths of the collected data is compared to prove the effectiveness of the algorithm.

Key words: in-vehicle LiDAR, point cloud, front-of-vehicle road extraction, feature fusion, differential

CLC Number:

P237

HE Guangming, HAN Shiyuan, CHEN Yuehui, ZHOU Jin, YANG Jun. Front-of-vehicle road extraction method based on feature fusion difference of vehicle LiDAR[J]. Bulletin of Surveying and Mapping, 2023, 0(12): 13-18.

References

[1] YUAN Xia,ZHAO Chunxia,ZHANG Haofeng. Road detection and corner extraction using high definition lidar[J]. Information Technology Journal,2010,9(5): 1022-1030.
[2] IBRAHIM S,LICHTI D. Curb-based street floor extraction from mobile terrestrial lidar point cloud[J]. ISPRS-International Archives of the Photogrammetry,Remote Sensing and Spatial Information Sciences,2012,B5(1): 193-198.
[3] YANG Bisheng,FANG Lina,LI J. Semi-automated extraction and delineation of 3D roads of street scene from mobile laser scanning point clouds[J]. ISPRS Journal of Photogrammetry and Remote Sensing,2013,79: 80-93.
[4] WANG Hanyun,LUO Huan,WEN Chenglu,et al. Road boundaries detection based on local normal saliency from mobile laser scanning data[J]. IEEE Geoscience and Remote Sensing Letters,2015,12(10): 2085-2089.
[5] GUAN Haiyan,LI J,YU Yongtao,et al. Automated road information extraction from mobile laser scanning data[J]. IEEE Transactions on Intelligent Transportation Systems,2015,16(1): 194-205.
[6] ZAI D,GUO Yulan,LI J,et al. 3D road surface extraction from mobile laser scanning point clouds[C]//Proceedings of 2016 IEEE Inter National Geoscience and Remote Sensing Symposium(IGARSS),[S.l.]:IEEE,2016.
[7] 于子龙,胡友健. 基于机载LiDAR点云的初始道路提取[J]. 激光与光电子学进展,2021,58(24): 137-144.
[8] 方莉娜,杨必胜. 车载激光扫描数据的结构化道路自动提取方法[J]. 测绘学报,2013,42(2): 260-267.
[9] 王勇,曾祥强. 集成注意力机制和扩张卷积的道路提取模型[J]. 中国图象图形学报,2022,27(10): 3102-3115.
[10] 刘国栋,刘佳,刘浪. 一种基于机载LiDAR数据的山区道路提取方法[J]. 激光技术,2022,46(4): 466-473.
[11] 肖信峰. 车载激光点云道路及标线提取[D].合肥:合肥工业大学,2022.
[12] 周建,沈长表,束蝉方. 基于车载激光点云的道路路面提取[J]. 现代测绘,2021,44(6): 8-12.
[13] 盛君,孙晨辉,王杰,等. 基于车载激光点云的城市道路提取方法研究[J]. 地理信息世界,2022,29(3): 114-118.
[14] 徐安帝,王会峰,余炳伟,等. 基于车载LiDAR点云的道路提取方法[J]. 光学技术,2023,49(1): 29-33.
[15] ZHANG Keqi,CHEN S C,WHITMAN D,et al. A progressive morphological filter for removing nonground measurements from airborne LIDAR data[J]. IEEE Transactions on Geoscience and Remote Sensing,2003,41(4): 872-882.
[16] QI C R,SU Hao,MO Kaichun,et al. PointNet: deep learning on point sets for 3D classification and segmentation[EB/OL]. [2023-06-01]. https://arxiv.org/abs/1612.00593.
[17] YOU Yurong,LUO K Z,CHEN Xiangyu,et al. Hindsight is 20/20: leveraging past traversals to aid 3D perception[EB/OL]. [2023-06-01]. https://arxiv.org/abs/2203.11405.
[18] DIAZ-RUIZ C A,XIA Youya,YOU Yurong,et al. Ithaca365: dataset and driving perception under repeated and challenging weather conditions[EB/OL]. [2023-06-01]. https://arxiv.org/abs/2208.01166.
[19] YOU Yurong,LUO K Z,PHOO C P,et al. Learning to detect mobile objects from LiDAR scans without labels[EB/OL]. [2023-06-01]. https://arxiv.org/abs/2203.15882.
[20] CLODE S,FRANZ R, PETER K,et al. Detection and vectorization of roads from lidar data[J]. Photogrammetric Engineering & Remote Sensing,2007,73(5): 517-535.
[21] WANG H,WANG C,CHEN Y,et al. Extracting Road Surface from Mobile Laser Scanning Point Clouds in Large Scale Urban Environment[C]//Proceedings of 17th International IEEE Conference on Intelligent Transportation SystemsⅡ.Yokohama:[s.n.],2014:673-678.