[1] Zhang Z, Wang J. Research on laser accurate detection method of lane line based on deep learning[J]. Laser Journal, 43, 53-57(2022).

[2] Wang Y B, Jin Y L, Zhang Y et al. Structured road obstacle detection method based on Lidar[J]. Journal of Chinese Inertial Technology, 31, 593-600, 619(2023).

[3] Xiong W C, Yang B S, Dong Z. Refining and robust extraction of roads from mobile laser scanning point clouds[J]. Journal of Geo-Information Science, 18, 376-385(2016).

[4] Mi X X, Yang B S, Dong Z et al. Automated 3D road boundary extraction and vectorization using MLS point clouds[J]. IEEE Transactions on Intelligent Transportation Systems, 23, 5287-5297(2022).

[5] Sha Z C, Chen Y P, Lin Y B et al. A supervoxel approach to road boundary enhancement from 3-D LiDAR point clouds[J]. IEEE Geoscience and Remote Sensing Letters, 19, 6500405(2022).

[6] Wang G J, Wu J, He R et al. A point cloud-based robust road curb detection and tracking method[J]. IEEE Access, 7, 24611-24625(2019).

[7] Sun P P, Zhao X M, Xu Z G et al. A 3D LiDAR data-based dedicated road boundary detection algorithm for autonomous vehicles[J]. IEEE Access, 7, 29623-29638(2019).

[8] Duan J M, Li S Y, Wang C R et al. Detection of road boundaries and obstacles based on lidar[J]. Applied Laser, 38, 1000-1007(2018).

[9] Chen J J, Pi D W, Xie B Y et al. Curb recognition algorithm based on geometric characters and 3D point cloud features[J]. Journal of Hebei University of Science and Technology, 40, 461-468(2019).

[10] Wang C, Kong B, Yang J et al. An algorithm for road boundary extraction and obstacle detection based on 3D lidar[J]. Pattern Recognition and Artificial Intelligence, 33, 353-362(2020).

[11] Hong J W. High-precision extraction of urban road markings based on 3D laser point cloud[J]. Geomatics Technology and Equipment, 24, 62-69(2022).

[12] Lin C Y, Guo Y Z, Li W J et al. An automatic lane marking detection method with low-density roadside LiDAR data[J]. IEEE Sensors Journal, 21, 10029-10038(2021).

[13] Ma L F, Li Y, Li J et al. Generation of horizontally curved driving lines in HD maps using mobile laser scanning point clouds[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12, 1572-1586(2019).

[14] Ye C M, Zhao H, Ma L F et al. Robust lane extraction from MLS point clouds towards HD maps especially in curve road[J]. IEEE Transactions on Intelligent Transportation Systems, 23, 1505-1518(2022).

[15] Hu J, Chen N, Xu W C et al. Three-dimensional lane detection algorithm of lidar based on adaptive gating and dual pathways[J]. Chinese Journal of Lasers, 50, 2210001(2023).

[16] Li W G, Fan X, Mei Y et al. Road marking extraction method based on vehicle laser point cloud[J]. Chinese Journal of Lasers, 49, 0710001(2022).

[17] Lei X D, Guan H Y, Chen K et al. Mobile laser scanning point cloud classification method based on data enhancement and mask learning[J]. Chinese Journal of Lasers, 51, 1310004(2024).

[18] Zhang C Y, Han L. Obstacle detection of LiDAR based on optimized DBSCAN[J]. Laser & Optoelectronics Progress, 59, 2428005(2022).

[19] Chang L L. Research on lane line detection mathod based on LIDAR[D](2019).

[20] Vallet B, Brédif M, Serna A et al. TerraMobilita/iQmulus urban point cloud analysis benchmark[J]. Computers and Graphics, 49, 126-133(2015).

[21] Papon J, Abramov A, Schoeler M et al. Voxel cloud connectivity segmentation-supervoxels for point clouds[C], 2027-2034(2013).

[22] Lin Y, Wang C, Zhai D et al. Toward better boundary preserved supervoxel segmentation for 3D point clouds[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 143, 39-47(2018).