Fast Visibility Analysis and Application in Road Environment with Mobile Laser Scanning Data
-
摘要: 传统的可视域分析方法需借助高精度三维模型,而目前三维模型构建的自动化水平、精度和完整度等很难满足道路环境可视域分析的要求。车载激光扫描系统可以高速度、高密度、高精度地获取道路及两侧地物的位置和属性信息(如反射强度、回波波形等),为大规模道路场景可视域计算与分析提供了一种全新的技术手段。借助深度缓存算法,提出了一种基于三维激光点云数据的可视域快速、稳健计算方法。该方法在典型道路地物要素提取的基础上,动态构建视场空间索引,实现了道路场景中任意位置可视域的快速、稳健估计,可广泛应用于交通标志牌遮挡分析、路灯有效照明区域计算和建筑物可视绿地面积估计等,为基础设施科学安置及运行健康状况监测、城市形态分析与城市规划等提供科学的辅助决策。Abstract: Visibility analysis is one of the most important parts of the spatial analysis in geographic information system, which is calculated based on the measurable models. However, it is hard to construct accurate models for the huge number of objects automatically because there is a mess of various objects in the urban area. Mobile laser scanning can acquire accurate three-dimensional information together with other physical properties (such as reflected intensity, echo waveform, etc.) on road and along roadside flexibly and efficiently, which provides an alternative data source for visibility analysis of the large-scale road scenes. This paper proposes a fast and robust depth-buffering method to analyze visibility based on point cloud data in road scenes efficiently and robustly. To achieve the goal, an adaptive spatial index construction strategy is firstly introduced based on the viewpoint and the corresponding field of view. Then the viewshed between the viewpoint and the field of view is analyzed efficiently using the depth-buffering method. The visualizing degree from the road to the traffic sign and the illuminated region on road of the street lamps are estimated respectively to verify the feasibility as well as the flexibility of the proposed method. The performance of the experiments shows that the proposed method can assist in monitoring the infrastructure health and decision support for the municipal planning department.
-
-
表 1 实验参数
Table 1 Experiment Parameters
参数名称 参数意义 参数取值/m gl 根结点格网长度 0.5 gw 根结点格网宽度 0.5 vx 叶子结点体素长度 0.25 vy 叶子结点体素宽度 0.25 vz 叶子结点体素高度 0.25 dx 深度缓存平面格网长度 0.25 dy 深度缓存平面格网宽度 0.25 表 2 有效区域的路面照度参数
Table 2 Parameters of Road Illumination in Valid Region
实验区域参数 单灯 相邻两灯 有效区域宽度/m 12.12 12.12 有效区域长度/m 45.03 81.23 有效区域内路面照度最大值/lx 26.67 27.51 有效区域内路面照度最小值/lx 17.68 17.68 有效区域内照度平均值/lx 20.81 21.57 -
[1] 李清泉.从Geomatics到Urban Informatics[J].武汉大学学报·信息科学版, 2017, 42(1): 1-6 http://ch.whu.edu.cn/CN/abstract/abstract5628.shtml Li Qingquan. From Geomatics to Urban Informatics[J]. Geomatics and Information Science of Wuhan University, 2017, 42(1): 1-6 http://ch.whu.edu.cn/CN/abstract/abstract5628.shtml
[2] 裴玉龙, 马骥.道路交通事故道路条件成因分析及预防对策研究[J].中国公路学报, 2003, 16(4): 77-82 doi: 10.3321/j.issn:1001-7372.2003.04.017 Pei Yulong, Ma Ji. Research on Countermeasures for Road Condition Causes of Traffic Accidents[J]. China Journal of Highway and Transport, 2003, 16(4): 77-82 doi: 10.3321/j.issn:1001-7372.2003.04.017
[3] Huang P, Cheng M, Chen Y, et al. Traffic Sign Occlusion Detection Using Mobile Laser Scanning Point Clouds[J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 18(9): 2 364-2 376 doi: 10.1109/TITS.2016.2639582
[4] Harris M. Documents Confirm Apple is Building Self-driving Car[J]. The Guardian, 2015, 14(8): 1-3
[5] Gomes L. When will Google's Self-driving Car Really be Ready?[J]. IEEE Spectrum, 2016, 53(5): 13-14 doi: 10.1109/MSPEC.2016.7459105
[6] 于占波.福田与百度合作:瞄准车联网和无人驾驶[J].商用汽车, 2016 (11): 50-51 doi: 10.3969/j.issn.1009-4903.2016.11.011 Yu Zhanbo. Foton and Baidu Join Hands Aiming to Internet of Vehicle and Driverless Vehicles[J]. Commercial Vehicle, 2016 (11): 50-51 doi: 10.3969/j.issn.1009-4903.2016.11.011
[7] Paden B, Čap M, Yong S Z, et al. A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles[J]. IEEE Transactions on Intelligent Vehicles, 2016, 1(1): 33-55 doi: 10.1109/TIV.2016.2578706
[8] 王嘉亮.道路照明设计中交通安全性的影响因素分析——基于驾驶员视觉特性的研究[J].建筑电气, 2006, 25(1): 33-35 http://d.old.wanfangdata.com.cn/Periodical/jzdq200601010 Wang Jialiang. Analysis on the Influencing Factors of Traffic Safety in Road Lighting Design—Based on the Drivers' Visual Characteristics[J]. Building Electricity, 2006, 25(1): 33-35 http://d.old.wanfangdata.com.cn/Periodical/jzdq200601010
[9] Popelka S, Vozenilek V. Landscape Visibility Analysis and Their Visualization[C]. The 1st International Workshop on Pervasive Web Mapping, Geoprocessing and Services, Como, Italy, 2010
[10] 卢秀山, 李清泉, 冯文灏, 等.车载式城市信息采集与三维建模系统[J].武汉大学学报(工学版), 2003, 36(3):76-80 http://d.old.wanfangdata.com.cn/Periodical/whsldldxxb200303017 Lu Xiushan, Li Qingquan, Feng Wenhao, et al. Vehicle-Borne Urban Information Acquisition and 3D Modeling System[J]. Engineering Journal of Wuhan University, 2003, 36(3): 76-80 http://d.old.wanfangdata.com.cn/Periodical/whsldldxxb200303017
[11] 张斌, 张泽建, 郭黎, 等.基于DEM的地形可视域分析关键技术[J].计算机科学, 2013, 40(9):284-287 doi: 10.3969/j.issn.1002-137X.2013.09.063 Zhang Bin, Zhang Zejian, Guo Li, et al. Key Technologies of Terrain Viewshed Analysis Based on DEM[J]. Computer Science, 2013, 40(9):284-287 doi: 10.3969/j.issn.1002-137X.2013.09.063
[12] 孙永, 王青山, 吴官祥.地形可视域的TIN切片计算方法[J].测绘科学技术学报, 2014, 31(1):8-12 doi: 10.3969/j.issn.1673-6338.2014.01.003 Sun Yong, Wang Qingshan, Wu Guanxiang. Slicing Calculation Method of Terrain Viewshed Based on the TIN[J]. Journal of Geomatics Science and Technology, 2014, 31(1):8-12 doi: 10.3969/j.issn.1673-6338.2014.01.003
[13] Katz S, Tal A. On the Visibility of Point Clouds[C]. IEEE International Conference on Computer Vision, Santiago, Chile, 2015
[14] Alsadik B, Gerkke M, Vosselman G. Visibility Analysis of Point Cloud in Close Range Photogrammetry[J]. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014, 2(5): 9-16 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=Doaj000003902965
[15] Rusu R B, Cousins S. 3D is Here: Point Cloud Library (PCL)[C]. IEEE International Conference on Robotics and Automation, Shanghai, China, 2011
[16] 张蕊, 李广云, 王力, 等.车载LiDAR点云混合索引新方法[J].武汉大学学报·信息科学版, 2018, 43(7): 993-999 http://ch.whu.edu.cn/CN/abstract/abstract6144.shtml Zhang Rui, Li Guangyun, Wang Li, et al. A New Method of Hybrid Index for Mobile LiDAR Point Cloud Data[J]. Geomatics and Information Science of Wuhan University, 2018, 43(7): 993-999 http://ch.whu.edu.cn/CN/abstract/abstract6144.shtml
[17] Yang B, Dong Z, Zhao G, et al. Hierarchical Extraction of Urban Objects from Mobile Laser Scanning Data [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015, 99: 45-57 doi: 10.1016/j.isprsjprs.2014.10.005
[18] 罗元, 毛建伟. LED路灯配光方案研究[J].灯与照明, 2011, 25(2): 43-46 doi: 10.3969/j.issn.1008-5521.2011.02.010 Luo Yuan, Mao Jianwei. Research on Light Distribution Schemes for LED Street Light[J]. Light & Lighting, 2011, 25(2): 43-46 doi: 10.3969/j.issn.1008-5521.2011.02.010
[19] 邢海英, 高铁成. LED路灯光学设计与分析[J].电工技术学报, 2015, 30(2): 242-247 doi: 10.3969/j.issn.1000-6753.2015.02.032 Xing Haiying, Gao Tiecheng. LED Road Lighting Optics Illumination and Analysis[J]. Transactions of China Electrotechnical Society, 2015, 30(2): 242-247 doi: 10.3969/j.issn.1000-6753.2015.02.032
[20] 李佳.城市绿地的作用[J].科技创新导报, 2008(33):77 doi: 10.3969/j.issn.1674-098X.2008.33.058 Li Jia. The Effects of the Urban Green Space[J]. Science and Technology Innovation Herald, 2008(33):77 doi: 10.3969/j.issn.1674-098X.2008.33.058
-
期刊类型引用(30)
1. 刘焱雄,陈义兰,杨龙,高珊. 基于测绘学角度探讨海岸线及其测定方法. 海洋科学进展. 2024(03): 425-436 . 百度学术
2. 王继鹏,金云智,辛忠华,吉才宇,郭龙. 基于PSO-BP的北斗卫星导航海底高程拟合技术的研究. 天然气与石油. 2024(06): 153-160 . 百度学术
3. 付五洲,许宝华,陆彬,李涛. 重力场模型在长江口岛礁垂直基准建立中的应用. 现代测绘. 2023(04): 57-60 . 百度学术
4. 王双喜,肖强,孙雪洁. 复杂海域高精度海底地形测量关键问题研究. 海洋技术学报. 2022(01): 7-12 . 百度学术
5. 周颖,王瑞. 远海PPK测量潮位用于深度基准面计算的研究. 港工技术. 2022(02): 23-26 . 百度学术
6. 柯灝,赵建虎,周丰年,吴敬文,暴景阳,赵祥伟,谢朋朋. 联合大地水准面、海面地形和潮波运动数值模拟的长江口陆海垂直基准转换关系. 武汉大学学报(信息科学版). 2022(05): 731-737+746 . 百度学术
7. 单瑞,李浩军,刘慧敏,赵钊,董凌宇,杜凯. GNSS PPP/INS紧组合模式下的远海无验潮水深测量. 海洋地质前沿. 2022(10): 87-93 . 百度学术
8. 张颖,闫玉茹,章家保,李静,裘露露. 潮滩冲淤观测技术发展现状. 海洋科学. 2021(03): 152-162 . 百度学术
9. 王森,刘立龙,黄良珂,周威. 基于潮汐调和分析的全球定位系统-多路径反射测量技术潮位预报. 科学技术与工程. 2021(09): 3481-3486 . 百度学术
10. 魏荣灏,陈佳兵,徐达. 基于PPK无验潮的水下地形测量技术研究. 海洋技术学报. 2021(01): 57-62 . 百度学术
11. 王挺,王萃. GNSS-PPK在远距离潮位观测的应用研究. 江西测绘. 2021(04): 8-11 . 百度学术
12. 王正杰,王峰,吴自银,曹振轶,罗孝文,李守军. 基于GPS PPK技术确定测深点瞬时潮位及分析. 海洋技术学报. 2020(02): 58-63 . 百度学术
13. 王小刚,赵薛强,许军. 珠江口瞬时水位解算方法研究及应用. 水利水电技术. 2020(11): 117-124 . 百度学术
14. 梁冠辉,陶常飞,周兴华,周东旭,王朝阳. 新型远距离验潮系统集成设计与研制. 海洋科学进展. 2019(01): 129-139 . 百度学术
15. 王智明,孙月文. 无验潮模式下的宁波杭州湾水下地形测量. 城市勘测. 2019(02): 157-159 . 百度学术
16. 陈正伟,韩磊. 基于高精度GNSS定位解算及姿态数据获取潮位研究. 海洋技术学报. 2019(05): 55-59 . 百度学术
17. 李梦昊,王胜利,高兴国,陈冠旭,刘焱雄. 基于混合编程的实时精密单点定位方法. 海岸工程. 2018(01): 66-73 . 百度学术
18. 黄辰虎,陆秀平,边刚,黄贤源,管明雷,翟国君,黄谟涛. 中短期验潮站验潮零点不规则漂移精密处理. 武汉大学学报(信息科学版). 2018(11): 1673-1680 . 百度学术
19. Yuanxi YANG,Tianhe XU,Shuqiang XUE. Progresses and Prospects of Marine Geodetic Datum and Marine Navigation in China. Journal of Geodesy and Geoinformation Science. 2018(01): 16-24 . 必应学术
20. 臧建飞,范士杰,易昌华,秦学彬,华亮,麻德明. 实时精密单点定位的远海实时GPS潮汐观测. 测绘科学. 2017(06): 155-160 . 百度学术
21. 臧建飞,范士杰,易昌华,秦学彬,陈冠旭,华亮. 远海实时GPS潮汐的实时精密单点定位观测. 测绘科学. 2017(08): 79-84 . 百度学术
22. 杨元喜,徐天河,薛树强. 我国海洋大地测量基准与海洋导航技术研究进展与展望. 测绘学报. 2017(01): 1-8 . 百度学术
23. 赵建虎,欧阳永忠,王爱学. 海底地形测量技术现状及发展趋势. 测绘学报. 2017(10): 1786-1794 . 百度学术
24. 王朝阳,周兴华,李延刚,梁冠辉,付延光. 远距离GNSS潮位测量精度的影响因素研究. 海洋技术学报. 2017(03): 1-6 . 百度学术
25. 辛保稳,李友龙. GPS PPK技术在海底地形测量中的应用. 科技展望. 2017(18): 161 . 百度学术
26. 杨涛,葛俊洁,李路. GPS测量技术及其在工程测量中的应用. 电子测试. 2016(06): 126+125 . 百度学术
27. 暴景阳,翟国君,许军. 海洋垂直基准及转换的技术途径分析. 武汉大学学报(信息科学版). 2016(01): 52-57 . 百度学术
28. 周东旭,周兴华,梁冠辉,王朝阳,杨磊. GPS浮标天线高的动态标定方法. 测绘科学. 2015(12): 121-124 . 百度学术
29. 赵建虎,王爱学. 精密海洋测量与数据处理技术及其应用进展. 海洋测绘. 2015(06): 1-7 . 百度学术
30. 赵元元,殷行. 土地测量中GPS实时动态技术的应用研究. 价值工程. 2015(20): 161-162 . 百度学术
其他类型引用(6)