Real-time measurement of track curvature based on vehicle attitude perception

Track curvature is a key parameter in many active control systems for rail vehicles. The real-time autonomous acquisition of track curvature is currently an engineering challenge in the field of rail transit. In this study, the cause of the geometric inertia effect (GIE) when the car body attitude is used to perceive the track curvature was explained by a theoretical derivation using the plane trajectory equation of the rail vehicle. Then, the bogie attitude rather than car body attitude was selected as the sensing signal due to weak GIE. In addition, a new algorithm for measuring the track curvature in real-time using the bogie yaw angular rate and the running velocity was proposed by combining the curvature compensation algorithm (CCA) and percentile filtering (PF) algorithm. Subsequently, the effectiveness of the proposed algorithm was verified through simulations. The results demonstrated that the proposed algorithm could effectively improve the measurement accuracy of the track curvature. Finally, the algorithm proposed in this study was validated based on running tests. The results of this study can provide a reference for the real-time measurement of track curvature.