Journal of Jilin University(Engineering and Technology Edition) ›› 2021, Vol. 51 ›› Issue (1): 206-216.doi: 10.13229/j.cnki.jdxbgxb20190836

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Visual detection method for vehicle braking time sequence based on slip rate identification

Dao WU1(),Li-bin ZHANG1(),Yun-xiang ZHANG2,Hong-ying SHAN3,Hong-mei SHAN1   

  1. 1.College of Transportation,Jilin University,Changchun 130022,China
    2.College of Biological and Agricultural Engineering,Jilin University,Changchun 130022,China
    3.School of Mechanical and Aerospace Engineering,Jilin University,Changchun 130022,China
  • Received:2019-08-24 Online:2021-01-01 Published:2021-01-20
  • Contact: Li-bin ZHANG E-mail:wudao16@mails.jlu.edu.cn;zlb@jlu.edu.cn

Abstract:

To overcome the shortcomings of existing braking performance testing methods, a non-contact dynamic testing method for vehicle braking time sequence was proposed. Based on the relationship between slip rate and adhesion coefficient, a measurement target of braking time sequence based on slip rate was put forward. Based on the measurement principle of binocular stereo vision, a measurement model for wheel slip rate based on vision was established. With the help of LM (Levenberg-Marquardt) algorithm, the calibration parameters were optimized nonlinearly. Image processing techniques such as pseudo-median bilateral filtering, Canny edge detection, redundant boundary clearance and Hough transform were used to denoise, extract edges, simplify and extract features respectively, by which the central coordinates of circular markers were obtained. To verify the feasibility of the proposed method, a real-time test was carried out and the standard uncertainty evaluation results of measurement errors were given. The results show that the maximum relative error of the proposed method was 2.74% and the maximum repeatability error was 3.88% under the conditions of U=2.52 and k=2.

Key words: vehicle engineering, tractor-semitrailer, braking time sequence, stereo vision, Levenberg-Marquardt algorithm, uncertainty

CLC Number: 

  • U472.9

Fig.1

Graph of adhesion coefficient and slip rate"

Fig.2

Measurement principle of binocular stereo vision"

Fig.3

Measurement model of wheel slip rate"

Fig.4

Motion trail of wheel circular marker"

Fig.5

Correction model of curve driving"

Fig.6

Calibration image pairs captured by binocular cameras"

Table 1

Internal and external parameters of binocular cameras"

参数左摄像机右摄像机
Kαx(像素)2515.24672517.5498
αy(像素)2513.10342514.3697
u0(像素)513.2687512.4456
v0(像素)381.1249382.6125
Kck1,k2-0.0551,0.0265-0.0426,-0.0254
R0.9998-0.0141?-0.01520.00550.9986-0.0017-0.0047-0.00570.9972
T[-402.1589-6.21474.5368]

Fig.7

Distribution map of reprojection error"

Fig.8

Circular markers′ image captured by binocular cameras"

Fig.9

Design sketch of pseudo-median bilateral filtering"

Fig.10

Canny edge detection"

Fig.11

Redundant boundary clearance and centroid coordinate extraction for circular markers"

Fig.12

Overall layout of vehicle braking time sequence detection system"

Fig.13

Wheel speed signal acquisition unit"

Table 2

Real vehicle test data and test results"

检测方法编号一轴二轴三轴四轴五轴六轴
左轮右轮左轮右轮左轮右轮左轮右轮左轮右轮左轮右轮
本文方法10.760.770.970.990.930.920.720.740.820.841.121.08
20.780.770.950.980.910.920.710.730.850.831.101.09
30.750.780.981.010.920.930.730.750.830.841.141.12
轮速信号采集单元10.770.780.960.970.920.920.730.720.830.841.111.09
20.790.780.960.980.910.930.720.720.840.841.121.11
30.760.770.980.990.920.920.740.730.830.851.141.12

Table 3

Evaluation results of standard uncertainty"

轴数合成标准不确定度u(δ)/%

拓展不确定度

U/%

置信因子k
一轴左轮1.222.442
右轮1.232.46
二轴左轮1.242.48
右轮1.252.5
三轴左轮1.242.48
右轮1.242.48
四轴左轮1.222.44
右轮1.222.44
五轴左轮1.232.46
右轮1.232.46
六轴左轮1.262.52
右轮1.262.52
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