[1] Chen TT, DaiB, Liu DX, et al. LIDAR-based long range road intersection detection[C]∥2011 Sixth International Conference on Image and Graphics, August 12-15, 2011, Hefei, Anhui, China. New York: IEEE, 2011: 754- 759.

[2] DouillardB, UnderwoodJ, MelkumyanN, et al. Hybrid elevation maps: 3D surface models for segmentation[C]∥2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 18-22, 2010, Taipei, Taiwan. New York: IEEE, 2010: 1532- 1538.

[3] 谢德胜, 徐友春, 王任栋, 等. 基于三维激光雷达的无人车障碍物检测与跟踪[J]. 汽车工程, 2018, 40(8): 952-959.

    Xie D S, Xu Y C, Wang R D, et al. Obstacle detection and tracking for unmanned vehicles based on 3D laser radar[J]. Automotive Engineering, 2018, 40(8): 952-959.

[4] 辛煜, 梁华为, 梅涛, 等. 基于激光传感器的无人驾驶汽车动态障碍物检测及表示方法[J]. 机器人, 2014, 36(6): 654-661.

    Xin Y, Liang H W, Mei T, et al. Dynamic obstacle detection and representation approach for unmanned vehicles based on laser sensor[J]. Robot, 2014, 36(6): 654-661.

[5] 程子阳, 任国全, 张银. 基于马尔可夫随机场的植被环境中的障碍物识别[J]. 激光与光电子学进展, 2019, 56(3): 031010.

    Cheng Z Y, Ren G Q, Zhang Y. Obstacle recognition in vegetation environment based on Markov random field[J]. Laser & Optoelectronics Progress, 2019, 56(3): 031010.

[6] BehleyJ, SteinhageV, Cremers AB. Efficient radius neighbor search in three-dimensional point clouds[C]∥2015 IEEE International Conference on Robotics and Automation (ICRA), May 26-30, 2015, Seattle, WA, USA. New York: IEEE, 2015: 3625- 3630.

[7] 范小辉, 许国良, 李万林, 等. 基于深度图的三维激光雷达点云目标分割方法[J]. 中国激光, 2019, 46(7): 0710002.

    Fan X H, Xu G L, Li W L, et al. Target segmentation method for three-dimensional lidar point cloud based on depth image[J]. Chinese Journal of Lasers, 2019, 46(7): 0710002.

[8] 袁夏, 赵春霞. 一种应用于机器人导航的激光点云聚类算法[J]. 机器人, 2011, 33(1): 90-96.

    Yuan X, Zhao C X. A laser point cloud clustering algorithm for robot navigation[J]. Robot, 2011, 33(1): 90-96.

[9] Liu Z, Wang J L, Liu D X. A new curb detection method for unmanned ground vehicles using 2D sequential laser data[J]. Sensors, 2013, 13(1): 1102-1120.

[10] Kumar P. McElhinney C P, Lewis P, et al. An automated algorithm for extracting road edges from terrestrial mobile LiDAR data[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2013, 85: 44-55.

[11] 孙朋朋, 赵祥模, 徐志刚, 等. 基于3D激光雷达城市道路边界鲁棒检测算法[J]. 浙江大学学报(工学版), 2018, 52(3): 504-514.

    Sun P P, Zhao X M, Xu Z G, et al. Urban curb robust detection algorithm based on 3D-LIDAR[J]. Journal of Zhejiang University(Engineering Science), 2018, 52(3): 504-514.

[12] Zhou L, Vosselman G. Mapping curbstones in airborne and mobile laser scanning data[J]. International Journal of Applied Earth Observation and Geoinformation, 2012, 18: 293-304.

[13] 周智, 蔡自兴, 余伶俐. 基于直线特征提取的自主车辆可通行区域检测[J]. 华中科技大学学报(自然科学版), 2011, 39(S2): 188-191.

    Zhou Z, Cai Z X, Yu L L. Line extraction for drivable road region detection on autonomous vehicle[J]. Journal of Huazhong University of Science and Technology. Nature Science, 2011, 39(S2): 188-191.

[14] 王晓辉, 吴禄慎, 陈华伟, 等. 基于区域聚类分割的点云特征线提取[J]. 光学学报, 2018, 38(11): 1110001.

    Wang X H, Wu L S, Chen H W, et al. Feature line extraction from a point cloud based on region clustering segmentation[J]. Acta Optica Sinica, 2018, 38(11): 1110001.

[15] 李仁忠, 刘阳阳, 杨曼, 等. 基于改进的区域生长三维点云分割[J]. 激光与光电子学进展, 2018, 55(5): 051502.

    Li R Z, Liu Y Y, Yang M, et al. Three-dimensional point cloud segmentation algorithm based on improved region growing[J]. Laser & Optoelectronics Progress, 2018, 55(5): 051502.

[16] 惠振阳, 程朋根, 官云兰, 等. 机载LiDAR点云滤波综述[J]. 激光与光电子学进展, 2018, 55(6): 060001.

    Hui Z Y, Cheng P G, Guan Y L, et al. Review on airborne LiDAR point cloud filtering[J]. Laser & Optoelectronics Progress, 2018, 55(6): 060001.

[17] HimmelsbachM, Hundelshausen FV, Wuensche HJ. Fast segmentation of 3D point clouds for ground vehicles[C]∥2010 IEEE Intelligent Vehicles Symposium, June 21-24, 2010, La Jolla, CA, USA. New York: IEEE, 2010: 560- 565.

[18] Zhang K Q, 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.