[1] Yingchun ZHANG, Zhihong HUANG. The development of intelligent transportation systems (ITS). Science & Technology Information, 494-495(2009).

[2] G J WANG, J WU, R HE. A point cloud-based robust road curb detection and tracking method. IEEE Access, 7, 24611-24625(2019).

[3] Zhiqiang HUANG, Jun LI. Research on environment perception technology of driverless car. The Magazine on Equipment Machinery, 1-6(2021).

[4] Kai ZHAO, Yuan ZHU, Rendong WANG. Mean elevation map-based ground segmentation method for 3D LIDAR point cloud under urban environment. Journal of Military Transportation University, 20, 80-84(2018).

[5] Jun SHENG, Chenhui SUN, Jie WANG et al. Research on urban road extraction method based on vehicle mounted laser point cloud. Geomatics World, 29, 114-118(2022).

[6] Xiru WU, Qiwei XIE. 3D vehicle detection for unmanned driving systerm based on lidar. Optics and Precision Engineering, 30, 489-497(2022).

[7] W WANG, C ZHAO, H ZHANG. A new method of ski tracks extraction based on laser intensity information. Applied Sciences, 12, 5678(2022).

[8] Dongsheng WANG. A method of obstacle detection on structured road environment. Computer & Digital Engineering, 50, 1494-1498(2022).

[9] Y LI, I JAVIER. LIDAR for autonomous driving: the principles, challenges, and trends for automotive lidar and perception systems. IEEE Signal Processing Magazine, 37, 50-61(2020).

[10] Liuzhao LI, Panling HUANG, Jun ZHOU et al. Multi-region segmentation 3D laser point cloud obstacle detection and application. Laser Journal, 43, 66-70(2022).

[11] Yaozu CHEN, Yuhai GU, Xia CHENG et al. Driving vehicle elements detection method based on optimized YOLOv4 algorithm. Journal of Applied Optics, 43, 248-256(2022).

[12] Shasha BAI, Haiyang ZHANG, Shidong XU et al. Slope extraction algorithm of ski tracks based on airborne LIDAR point cloud. Journal of Applied Optics, 42, 481-487(2021).

[13] C R QI, H SU, K MO et al. Pointnet: deep learning on point sets for 3d classification and segmentation, 652-660(2017).

[14] C T YIAKOPOULOS, K C GRYLLIAS, I A ANTONIADIS. Rolling element bearing fault detection in industrial environments based on a K-means clustering approach. Expert Systems with Applications, 38, 2888-2911(2011).

[15] Y CHEN, G LIU, Y XU et al. PointNet++ network architecture with individual point level and global features on centroid for ALS point cloud classification. Remote Sensing, 13, 472(2021).

[16] Zhenyan WANG, Hongyan SUN, Xiaopeng SUN. Survey on large scale 3D point cloud processing using deep learning. Computer Systems & Applications, 32, 1-12(2023).

[17] Xing ZHANG. Object detection and recognition of autonomous driving based on depth information and multiple feature vectors(2021).

[18] Chang LIU, Jin ZHAO, Zihao LIU et al. Improved LIDAR obstacle detection method based on euclidean clustering. Laser & Optoelectronics Progress, 57, 254-260(2020).

[19] Jingjing FAN, Li WANG, Shijian CHU et al. Research on pedestrian recognition in cross-country environment based on KDTree and Euclidean clustering. Automotive Engineering, 41, 1410-1415(2019).

[20] Desheng XIE, Youchun XU, Rendong WANG et al. Obstacle detection and tracking for unmanned vehicles based on 3D laser radar. Automotive Engineering, 40, 952-959(2018).

[21] Changfu ZONG, Long WEN, Lei HE. Object detection based on Euclidean clustering algorithm with 3D laser scanner. Journal of Jilin University(Engineering and Technology Edition), 50, 107-113(2020).

[22] L WEN, L HE, Z GAO et al. Research on 3D point cloud de-distortion algorithm and its application on Euclidean clustering. IEEE Access. 2019, 7, 86041-86053.

[23] R SAHA, G KUMAR, M K RAI et al. Adaptive classifier-based intrusion detection system using logistic regression and Euclidean distance on network probe vectors in resource constrained networks. International Journal of Information and Computer Security, 16, 226-229(2021).