西安交通大学电气工程学院,西安,710049
网络首发:2009-04-10,
纸质出版:2009
移动端阅览
杨建国, 刘勇, 贾凡. 从高空摄像中获取车辆瞬态信息和驾驶行为[J]. 西安交通大学学报, 2009,43(4):116-120.
Obtaining Transient Information of Vehicles and Behaviors of Drivers from High-Altitude Photography[J]. 2009, 43(4): 116-120.
针对交通冲突中车辆的避碰过程无法量化的问题
提出了基于全信息匹配的视频分析法.其核心是利用图像处理方法获得车辆的精确位置
并据此计算出车辆的速度、加速度、航向角、前轮转向角等瞬态信息
进而估算出驾驶人的变速和转向动作.这些测量是在驾驶人无察觉的情况下进行的.利用全信息匹配算法以及亚像素估计等算法
解决了因阳光阴影带来的轮廓边缘变化导致的位置偏移
以及摄像机像素不够的问题
实现了0.1像素级别的车辆位置精确求解.用经过校准的透射变换
消除了拍摄角度对结果的影响.在实验场地
对受试车辆进行了变速和转向实验
结果表明通过高空拍摄图像分析得到的驾驶人动作与实际记录的驾驶人动作完全吻合
且能发现人工没有记录但驾驶人确实承认的轻微转向动作.
A method called video analysis based on full information matching(FIM)is proposed to quantify the dynamic process of vehicles in avoiding collisions in traffic conflicts. The key point of the method is to obtain the exact position of the designated vehicle
and to calculate the transient information of the vehicle including its velocity
acceleration
course angles and front-wheel steering angle. Then the actions of the driver can be estimated
such as accelerating
decelerating
and swerving. All these measurements are taken without the drivers' awareness. Full information matching and sub-pixel estimation are used to eliminate the influence of vehicle contour changes on precision of vehicle positioning which are caused by the change of vehicle's shadow. Also the problem of camera's low pixels is solved by using these methods. The precision of vehicle positioning can be up to 0.1 pixel. An adjusted transmission transformation is used to eliminate the influence of shooting angle. A field experiment is carried out to obtain the driver's actions including shifting and swerving. It is proved that the driver's actions achieved by the analysis of high-altitude photography accord with the actual recording actions
and slight swervings that couldn't be observed or recorded artificially are caught as well.
CHIN H C, QUEK S T. Measurement of traffic conflicts [J]. Safety Science, 1997, 26(3): 169-185.
COIFMAN B, BEYMER D, MCLAUCHLAN P, et al. A real-time computer vision system for vehicle tracking and traffic surveillance[J]. Transportation Research: Part C, 1998, 6(4): 271-278.
HAN Xiaowei, LI Yanping, LI Junsheng, et al. An approach of color object searching for vision system of soccer robot[C]∥ Proceedings of the IEEE International Conference on Robotics and Biomimetics. Piscataway, NJ, USA: IEEE, 2004: 535-539.
WAKABAYASHI H, RENGE K. Vehicle tracking system using digital VCR and ITS application to traffic conflict analysis for ITS-assist traffic safety [C]∥ Proceedings of the 13th Mini-EURO Conference on Handling Uncertainty in the Analysis of Traffic and Transportation Systems. Bari, Italy: Euro Working Group on Urban Traffic and Transportation, 2002: 356-362.
杨建国,尹旭全,方丽,等. 基于自适应轮廓匹配的视频车辆检测和跟踪[J]. 西安交通大学学报,2005,39(4):351-355.
YANG Jianguo, YIN Xuquan, FANG Li, et al. Moving vehicle detection and tracking based on video of self-adaptive contour matching[J]. Journal of Xi'an Jiaotong University,2005,39(4):351-355.
李健. 基于视频的机动车冲突检测初步研究[D].西安:西安交通大学电气工程学院,2006.
金观昌. 计算机辅助光学测量[M]. 北京: 清华大学出版社, 1997:143-147.
郭荣鑫, 杨邦成, 蔡光程, 等. 亚像素位移插值计算方法的比较分析[J]. 昆明理工大学学报(理工版), 2005, 30(2): 55-59.
GUO Rongxin, YANG Bangcheng, CAI Guangchen, et al. Comparative analysis of the subpixel displacement calculation methods in the digital speckle measurement[J]. Journal of Kunming University of Science and Technology, 2005, 30(2):55-59.
孟利波, 马少鹏, 金观昌. 数字散斑相关测量中亚像素位移测量方法的比较[J]. 实验力学, 2003, 18(3): 343-348.
MENG Libo, MA Shaopeng, JIN Guanchang. On the performance of the subpixel displacement estimations used in digital speckle correlation method[J]. Journal of Experimental Mechanics, 2003, 18(3): 343-348.
贾凡. 基于视频目标精确跟踪的交通冲突检测方法研究[D].西安:西安交通大学电气工程学院,2008.
【本刊相关文献链接】
车辆单神经元模型参考自适应控制算法研究. 2007,41(12):1391-1395
基于视频的车辆瞬时停车延误检测. 2007,41(6):692-696
多约束条件车辆路径问题的二阶段遗传退火算法. 2005,39(12):1299-1302
自主车辆视觉系统的摄像机动态自标定算法. 2005,39(10):1072-1076
基于平方根Unscented卡尔曼滤波的车辆融合跟踪. 2005,39(6):594-597
0
浏览量
4
下载量
3
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621