凸凹不平道路几何参数识别和模型重构方法研究

doi:10.19562/j.chinasae.qcgc.2023.02.012

Abstract

Abstract:

For autonomous vehicles driving on uneven road and abnormal road， not only factors such as road curvature need to be considered， but also characteristics and diseases such as road bumps and potholes need to be identified and modeled， so as to improve vehicle passability， safety and comfort. Therefore， this paper proposes a surface geometry parameter recognition and model reconstruction method of uneven road based on the Lidar. Firstly， the Locally Weighted Scatterplot Smoothing （Lowess） method is applied to the lidar point cloud processing for the first time to improve the smoothness of the lidar point cloud data. Secondly， a surface geometry parameter recognition method based on slope threshold segmentation is proposed to identify and extract the road bumps and pits by setting slope threshold. Thirdly， the 3D mathematical model based on piecewise polynomial function with constraints for road surface geometry parameter of uneven road is built. Finally， through the indoor sand table model of typical characteristics of the road and the measured data， the road geometry parameters’ recognition and model reconstruction are carried out by the proposed method. The results show that the piecewise polynomial fitting method achieves the best fitting effect when the fitting times are 5-6 times， and the root mean square error of 92% data points in each scene is within the range of 0~0.015m. The proposed method can accurately achieve the surface geometric parameter identification of uneven road and realize the 3D mathematical model reconstruction of the typical geometry feature.

Key words: uneven road, model reconstruction, piecewise polynomial fitting, slope threshold, lidar

Wenguang Wu,Shuangyue Tian,Zhiyong Zhang,Bin Jin,Zenghua Qiu. Research on Surface Geometry Parameter Recognition and Model Reconstruction of Uneven Road[J].Automotive Engineering, 2023, 45(2): 273-284.

Figures/Tables 16

处理阶段	变量	取值
点云平滑	$α$ $β$ $θ$	25° 0° 0°
点云平滑	$K$	41
典型特征提取	$m$	4
	$[K m i n, K m a x]$	［-0.15，0.15］
	$σ$	5

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参数	数值
激光雷达
测量精度	±3 cm
垂直视角	-15°~15°
垂直分辨率	2°
水平视角	360°
水平分辨率	0.1°~0.4°
电子倾角仪
测量范围	单轴：360°、双轴：±40°
分辨率	0.02°
精度	±0.2°

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Research on Surface Geometry Parameter Recognition and Model Reconstruction of Uneven Road

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References 30

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