[1]陈嘉颖,黄晓明,郑彬双,等.基于近景摄影测量技术的沥青路面纹理实时识别系统[J].东南大学学报(自然科学版),2019,49(5):973-980.[doi:10.3969/j.issn.1001-0505.2019.05.022]
 Chen Jiaying,Huang Xiaoming,Zheng BinshuangZhao Runmin,et al.Real-time identification system of asphalt pavement texture based on close-range photogrammetry[J].Journal of Southeast University (Natural Science Edition),2019,49(5):973-980.[doi:10.3969/j.issn.1001-0505.2019.05.022]
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基于近景摄影测量技术的沥青路面纹理实时识别系统()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
49
期数:
2019年第5期
页码:
973-980
栏目:
材料科学与工程
出版日期:
2019-09-20

文章信息/Info

Title:
Real-time identification system of asphalt pavement texture based on close-range photogrammetry
作者:
陈嘉颖1黄晓明1郑彬双1赵润民1刘修宇1曹青青1朱晟泽12
1 东南大学交通学院, 南京 211189; 2 上海久事集团有限公司, 上海 200021
Author(s):
Chen Jiaying1 Huang Xiaoming1 Zheng Binshuang1Zhao Runmin1 Liu Xiuyu1 Cao Qingqing1 Zhu Shengze12
1 School of Transportation, Southeast University, Nanjing 211189, China
2 Shanghai Jiushi(Group)Co., Ltd., Shanghai 200021, China
关键词:
抗滑性能 自动化近景摄影测量系统 沥青路面纹理信息 平均构造深度 均方根粗糙度
Keywords:
anti-skid performance automatic close-range photogrammetry system asphalt pavement texture information mean texture depth root-mean-square roughness
分类号:
TU528.1
DOI:
10.3969/j.issn.1001-0505.2019.05.022
摘要:
为了实时获取沥青路面纹理信息并准确监测服役道路路面的抗滑性能,基于环形三相机近景摄影测量(CRP)技术提出并创建了一个获取沥青路面纹理信息的自动化近景摄影测量(ACRP)系统,实现了沥青路面表面纹理图像自动化采集及三维重建过程.首先对采集的路表纹理图像进行数值化处理;其次,在基于MATLAB与Python联合编程的三维重建模块中重建具有表面纹理的沥青路面三维模型,并提取沥青路面表面高程数据;最后,在三维重建模块中进行路表纹理指标参数的运算,并采用铺砂法、激光扫描法进行沥青路面纹理现场对比试验.结果表明,以平均构造深度与均方根粗糙度(RMSR)为路表纹理统计指标,ACRP系统获得的纹理信息具有较高的准确性与高效性,识别精度接近于0.02 mm.ACRP系统提高了传统近景摄影测量的工作效率和精度,可为后续无人驾驶车辆安全制动提供实时、有效的路表抗滑信息.
Abstract:
To obtain the asphalt pavement texture information in real time and monitor the anti-skid performance of the road pavement accurately, an automatic close-range photogrammetry system(ACRP system)was proposed and built based on the three circle-arranged camera close-range photogrammetry(CRP)technology. The automatic image acquisition and the three-dimensional(3D)reconstruction were completed using the ACRP system. Firstly, the collected pavement texture images were digitized. Secondly, a 3D model of asphalt pavement with surface texture was established in the 3D reconstruction software module based on MATLAB and Python joint programming. The surface elevation data of asphalt pavement were extracted. Finally, index parameters of the pavement surface texture were calculated in 3D reconstruction software. The sand patch and the laser scanning(ZGScan)were chosen to collect the on-site asphalt pavement texture for comparison. The mean texture depth(MTD)and the root-mean-square roughness(RMSR)were chosen as the statistical indicators of the pavement surface texture. The results show that the texture data obtained by ACRP system have relatively high accuracy and efficiency. The recognition accuracy of the ACRP system is close to 0.02 mm, providing real-time and effective anti-skid pavement surface information for subsequent safety braking of autonomous vehicles.

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备注/Memo

备注/Memo:
收稿日期: 2018-09-03.
作者简介: 陈嘉颖(1993—),男,硕士生;黄晓明(联系人),男,博士,教授,博士生导师,huangxm@seu.edu.cn.
基金项目: 国家自然科学基金资助项目(51778139)、江苏省普通高校研究生科研创新计划资助项目(KYCX18_0146, SJCX18_0046).
引用本文: 陈嘉颖,黄晓明,郑彬双,等.基于近景摄影测量技术的沥青路面纹理实时识别系统[J].东南大学学报(自然科学版),2019,49(5):973-980. DOI:10.3969/j.issn.1001-0505.2019.05.022.
更新日期/Last Update: 2019-09-20