基于参考坐标系的轨道交通车辆静态边界检测

Q4 Decision Sciences
L. Dong, S. Su, Wei Wang, Yuan-yuan Wang
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引用次数: 0

摘要

针对传统轨道交通车辆静态边界检测方法精度低、相对误差大的问题,提出了一种基于参考坐标系的轨道交通车辆静止边界检测方法。通过数学模型得到了测点的参数方程。通过建立基于激光跟踪的参考轨道坐标系来测量模型和边界。通过自校准多传感器系统校准和DGPS/IMU集成处理,计算出每个双目图像的内部和外部比特,并构造出立体图像中每个元素的相对关系。结合车辆边界,计算车辆边界参数,实现轨道交通车辆的静态边界检测。实验结果表明,该方法可以有效地提高车辆边界检测的精度,降低车辆边界检测相对误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Static boundary detection of rail transit vehicles based on reference coordinate system
Aiming at the problems of low accuracy and large relative error of traditional rail transit vehicle static boundary detection method, a method of rail transit vehicle static boundary detection based on reference coordinate system is proposed. The parametric equations of measuring points are obtained by mathematical model. The model and boundary are measured by establishing reference orbit coordinate system based on laser tracking. By using self-calibration multi-sensor system calibration and DGPS/IMU integrated processing, the internal and external bits of each binocular image are calculated, and the relative relations of each element in the stereo image are constructed. Combining with the vehicle boundary, the vehicle boundary parameters are calculated to realise the static boundary detection of rail transit vehicles. Experimental results show that this method can effectively improve the accuracy of vehicle boundary detection and reduce the relative error of vehicle boundary detection.
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来源期刊
International Journal of Applied Systemic Studies
International Journal of Applied Systemic Studies Decision Sciences-Information Systems and Management
CiteScore
1.10
自引率
0.00%
发文量
2
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