Research on spatial sight distance computing method based on aerial survey data

doi:10.16265/j.cnki.issn1003-3033.2018.02.007

Abstract

Abstract: The paper was aimed at exploring the influence of road spatial sight distance on the serious road traffic accidents. Firstly, a 3D model was built for the accident scene and the road shape data were restored according to the aerial image of the unmanned aerial vehicle. Then, a spatial sight distance computing method was worked out based on the 3D reconstruction model and the road shape restoration data. Next, an aerial survey data based spatial sight distance computing platform was built in Open Scene Graph(OSG). Finally, the method was used to analyzing a certain serious road accident which occurred in Guizhou in August 2016. The results show that the method worked out by the authors can be used to solve the spatial sight distance computing problems even if the road accessory facilities impacted the spatial sight distance, such as guardrail, signs and roadside landscape, impact the spatial sight distance, and road actual situation is inconsistent with the construction or as-built drawings.

Key words: serious road traffic accidents, aerial survey data, three dimensional reconstruction, data restoration, spatial sight distance computing

CLC Number:

X924.3

HAO Huilong, LI Pingfan, HUANG Gang, SONG Yaoxin. Research on spatial sight distance computing method based on aerial survey data[J]. China Safety Science Journal, 2018, 28(2): 40-44.

References

[1] 杨凯, 徐辉, 林伟. 平原区交叉口安全分析与改善对策研究[J]. 中国安全科学学报, 2006, 16(11): 37-41.
YANG Kai, XU Hui, LIN Wei. Research on safety analysis and improvement countermeasures of intersection in plain area[J]. China Safety Science Journal, 2006, 16(11): 37-41.
[2] 杜博英, 方守恩. 分段式三次抛物线的视距及设计方法[J]. 公路交通科技, 2002, 19(5): 45-47.
DU Boying, FANG Shouen. Sight distance and design method of the transitioned vertical curve[J]. Journal of Highway and Transportation Research and Development, 2002, 19(5): 45-47.
[3] 王福建, 曾学贵. 公路行车视距检验的三维表面模型方法[J]. 公路交通科技, 1999, 16(1): 20-22.
WANG Fujian, ZENG Xuegui. 3D surface model method for highway sight distance test[J]. Journal of Highway and Transportation Research and Development, 1999, 16(1): 20-22.
[4] 王佐, 刘建蓓, 郭腾峰. 公路空间视距计算方法与检测技术[J]. 长安大学学报:自然科学版, 2007, 27(6): 44-62.
WANG Zuo, LIU Jianbei, GUO Tengfeng. Calculating method and appraising technique of highway 3D-view sight distance[J]. Journal of Chang' an University: Natural Science Edition, 2007, 27(6): 44-62.
[5] 刘向阳, 刘建蓓, 郭腾峰. 公路虚拟仿真在M3项目上的应用[J]. 公路, 2008 (9): 66-69.
[6] 汪雅婕. Pix4Dmapper在无人机航摄应急救灾项目中的应用研究[J]. 测绘与空间地理信息, 2016, 39(9): 202-203.
WANG Yajie. Application of Pix4Dmapper in unmanned aerial vehicle (UAV) aerial photography emergency rescue project[J]. Mapping and Geospatial Information, 2016, 39(9): 202-203.
[7] 李平凡, 黄钢, 宋耀鑫, 等. 基于车路耦合方法的车辆制动失效影响分析[J]. 中国司法鉴定, 2017 (6): 61-67.
LI Pingfan, HUANG Gang, SONG Yaoxin, et al. Analysis of the effect of vehicle braking failure based on vehicle road coupling method[J]. China Forensic Identification, 2017 (6): 61-67.
[8] 潘兵宏, 赵一飞, 梁孝忠. 动视觉原理在公路线形设计中的应用[J]. 长安大学学报: 自然科学版, 2004, 24(6): 20-24.
PAN Binghong, ZHAO Yifei, LIANG Xiaozhong. Application of dynamic vision theory in highway alignment design[J]. Journal of Chang'an University: Natural Science Edition, 2004, 24(6): 20-24.
[9] 张殿业. 驾驶员动态视野与行车安全可靠度[J]. 西南交通大学学报, 2000, 35(3): 319-322.
ZHANG Dianye. Dynamic visual field of driver with safety driving[J]. Journal of Southwest Jiaotong University, 2000, 35(3): 319-322.
[10] 张弛, 杨少伟, 潘兵宏,等. 交通仿真中驾驶人空间视野感知模型[J]. 交通运输工程学报, 2010, 10(4): 115-120.
ZHANG Chi, YANG Shaowei, PAN Binghong, et al. Driver's spatial visual field perception model in traffic simulation[J]. Journal of Traffic and Transportation Engineering, 2010, 10(4): 115-120.
[11] 肖鹏, 刘更代, 徐明亮. Open Scene Graph三维渲染引擎编程指南[M]. 北京:清华大学出版社, 2010: 312-314.

[1]	HE Jing, HOU Na, ZHANG Changfan, HU Xinliang, LIU Jianhua. Diagnosis of train wheelset tread damage based on EPSA-ResNet [J]. China Safety Science Journal, 2022, 32(5): 35-40.
[2]	ZHANG Meng, HAN Yu, LIU Zefeng. Detection method of high-altitude safety protective equipment for construction workers based on deep learning [J]. China Safety Science Journal, 2022, 32(5): 140-146.
[3]	ZOU Rongwei, YANG Qiliang, XING Jianchun, LI Suliang, CHEN Wenjie, KONG Linlin. False alarm judgment method based on dynamic and static mixed data analysis: for building BIM operation and maintenance platforms [J]. China Safety Science Journal, 2021, 31(11): 163-170.
[4]	ZHANG Jufeng, SHI Shiliang, LU Yi, YOU Bo, WU Fanghua, WU Kuan. Intelligent early warning system of gas and coal spontaneous combustion disaster based on big data: data characteristics, application structure and key technologies [J]. China Safety Science Journal, 2021, 31(9): 60-66.
[5]	CHEN Chao, YAN Yan. Emergency plan drilling system based on disaster digital twin [J]. China Safety Science Journal, 2021, 31(7): 90-96.
[6]	GU Yingkui, LIU Ping, LIN Zhonghai, QIU Guangqi. Fault diagnosis method of rolling bearing based on Kurtogram and DSCN [J]. China Safety Science Journal, 2021, 31(6): 99-105.
[7]	WU Yilin, CHEN Xiaoming, ZHOU Feng, JIN Weifeng, YU Aiyan, WANG Zhengjia. Analysis and safety monitoring of multi-span reticulated shell construction platform [J]. China Safety Science Journal, 2021, 31(4): 119-124.
[8]	LI Jichao, GUO Shengyu, KONG Liulin, YUAN Yican, SUN Yang. Design and application of a fire detection and early warning robot in construction site [J]. China Safety Science Journal, 2021, 31(4): 141-146.
[9]	ZHANG Wei, LIAO Yangxin, JIANG Ling, ZHAO Tingsheng. Safety monitoring system of tower crane based on internet of things [J]. China Safety Science Journal, 2021, 31(2): 55-62.
[10]	LONG Shidan. Application of automatic operation system for high-speed railway [J]. China Safety Science Journal, 2020, 30(S1): 92-97.
[11]	ZHANG Tianbai, YANG Guoguang, LI Jun. Analysis on safty architecture and operation mode of PRT system [J]. China Safety Science Journal, 2020, 30(S1): 115-120.
[12]	JIA Baofeng, YAN Meihao. Research on safety early warning system of railway express freight [J]. China Safety Science Journal, 2020, 30(S1): 121-127.
[13]	LI Tingting, LU Cheng. Railway industry statistical survey system based on safety protection [J]. China Safety Science Journal, 2020, 30(S1): 133-138.
[14]	ZUO Zibo, PAN Xi, HUANG Yulin, WANG Xiaolin, ZHANG Longlong. Early warning indicators for safety monitoring and control of super high-rise ICCP [J]. China Safety Science Journal, 2020, 30(1): 53-60.
[15]	YU Gang, SHI Lihua. Tunnel emergency simulation and deduction system based on MR and microservice [J]. China Safety Science Journal, 2020, 30(1): 162-167.