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Static boundary detection of rail transit vehicles based on reference coordinate system

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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Applied Systemic Studies Inderscience Publishers

Static boundary detection of rail transit vehicles based on reference coordinate system

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1751-0589
eISSN
1751-0597
DOI
10.1504/IJASS.2020.108676
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

International Journal of Applied Systemic StudiesInderscience Publishers

Published: Jan 1, 2020

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