基于扩展卡尔曼滤波与机器视觉融合的道路侧向坡度估计

doi:10.19562/j.chinasae.qcgc.2024.04.006

Abstract

Abstract:

To address the difficulty of accurately estimating the lateral slope of the road ahead using existing algorithms， a road lateral slope estimation method based on the fusion of Extended Kalman Filter （EKF） and Machine Vision Based （VB） is proposed. Firstly， a two-degree of freedom model for vehicles with lateral slope is established， and the superposition state of lateral slope and vehicle roll angle is estimated through EKF， with the vehicle roll angle decoupled by multiplying the lateral acceleration with an appropriate gain to obtain the estimated lateral slope of the EKF road. Secondly， based on the principle of visual imaging， the geometric relationship between the lateral slope of roads in two-dimensional images and the relevant parameters in the images is analyzed to obtain an estimated value of the lateral slope of roads in VB. Finally， the final estimation of road lateral slope is obtained through data fusion， making the estimation results redundant and complementary. The simulation and actual vehicle test results show that the fusion algorithm can be applied to slopes with varying lateral slopes and significantly improve the estimation accuracy.

Key words: lateral slope, slope estimation, extended Kalman filter, machine vision, data fusion

Yunbing Yan,Minghao Yue,Haiwei Li. Estimation of Road Side Slope Based on Fusion of Extended Kalman Filter and Machine Vision[J].Automotive Engineering, 2024, 46(4): 605-616.

Figures/Tables 26

参数	符号	数值
质心到前轴的距离/mm	$l f$	1 040
质心到后轴的距离/mm	$l r$	1 560
整车质量/kg	$m$	1 110
车体绕z轴转动惯量/（ $k g ? m 2$ ）	$I z$	1 343.1
轮距/mm	$L t$	1 480
悬架安装宽度/mm	$l$	185

项目	EKF	VB-EKF
$M A E$ /%	0.20	0.11
$R M S E$ /%	0.26	0.14

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名称	型号
工控机	超恩ECX-1400
摄像头	汇博士X20
惯性导航仪	GNW-MKS4051

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Estimation of Road Side Slope Based on Fusion of Extended Kalman Filter and Machine Vision

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