融合滑移率校正的智能车辆定位方法

doi:10.19562/j.chinasae.qcgc.2025.05.006

Abstract

Abstract:

Accurate and reliable vehicle pose estimation is a critical input for intelligent vehicle decision， planning and motion control modules. In this paper， a positioning algorithm that integrates real-time slip ratio estimation and compensation for intelligent vehicles is proposed， which significantly enhances the fusion positioning accuracy of the Inertial Navigation System （INS） and Wheel Speed Sensor （WSS） during Global Navigation Satellite System （GNSS） interruption. Firstly， a real-time slip ratio estimation algorithm is proposed to correct the wheel speed information for different driving conditions， which uses vehicle acceleration and wheel speed data. Then， based on error-state Kalman filter （ESKF）， the corrected wheel speed data is fused with GNSS and Inertial Measurement Unit （IMU） information to achieve accurate and reliable vehicle pose estimation. The results of the real-vehicle experiments show that during GNSS interruption， the Root Mean Square Error （RMSE） of velocity improves by up to 30% and the average horizontal position error mileage ratio reaches 1.68‰.

Key words: intelligent vehicle, fusion positioning, slip ratio estimation, error-state Kalman filter

Lu Xiong,Jiaqi Zhu,Mengyuan Chen,Ziyao Li,Qiang Shu,Guirong Zhuo. Positioning Method Based on Slip Ratio Compensation for Intelligent Vehicles[J].Automotive Engineering, 2025, 47(5): 851-858.

Figures/Tables 12

References 22

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Positioning Method Based on Slip Ratio Compensation for Intelligent Vehicles

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