Measurement method of vehicle yaw rate with smartphone

CHEN Zhi-jun; WU Chao-zhong; HUANG Zhen; MA Jie; GAO Yan

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CHEN Zhi-jun, WU Chao-zhong, HUANG Zhen, MA Jie, GAO Yan. Measurement method of vehicle yaw rate with smartphone[J]. Journal of Traffic and Transportation Engineering, 2013, 13(6): 61-68.

Citation:

CHEN Zhi-jun, WU Chao-zhong, HUANG Zhen, MA Jie, GAO Yan. Measurement method of vehicle yaw rate with smartphone[J]. Journal of Traffic and Transportation Engineering, 2013, 13(6): 61-68.

CHEN Zhi-jun, WU Chao-zhong, HUANG Zhen, MA Jie, GAO Yan. Measurement method of vehicle yaw rate with smartphone[J]. Journal of Traffic and Transportation Engineering, 2013, 13(6): 61-68.

Citation:

CHEN Zhi-jun, WU Chao-zhong, HUANG Zhen, MA Jie, GAO Yan. Measurement method of vehicle yaw rate with smartphone[J]. Journal of Traffic and Transportation Engineering, 2013, 13(6): 61-68.

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Measurement method of vehicle yaw rate with smartphone

CHEN Zhi-jun^{1, 2
,},
WU Chao-zhong^{1, 2
,},
HUANG Zhen^{2, 3},
MA Jie^{1, 2},
GAO Yan⁴

1.
Research Center of Intelligent Transportation System, Wuhan University of Technology, Wuhan 430063, Hubei, China
2.
Engineering Research Center of Ministry of Education for Waterway and Highway Transportation Safety Control and Equipment, Wuhan University of Technology, Wuhan 430063, Hubei, China
3.
School of Automation, Wuhan University of Technology, Wuhan 430063, Hube, China
4.
National Research Center of Engineering and Technology for Road Traffic Management, Traffic Management Science Research Institute of Ministry of Public Security, Wuxi 214151, Jiangsu, China

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Author Bio:
CHEN Zhi-jun(1983-), male, doctoral student, +86-27-86582280, chenzj556@163.com

WU Chao-zhong(1972-), male, professor, PhD, +86-27-86582280, chaozhongwu@126.com
Received Date: 2013-08-18
Publish Date: 2013-12-25

Abstract

Abstract

Vehicle yaw rates were measured by smartphone and high-precision inertial navigation system (INS). The influence of smartphone places on the measurement accuracy of yaw rate was analyzed. A self-adaptive weighted fusion algorithm was applied to reduce the measurement error of built-in gyroscope and orientation sensor of smartphone. The extreme value theory of multivariable function was used to obtain the optimal weighting factors of two sensors. The best value of yaw rate was calculated by weighted summation. Analysis result indicates that the impact of smartphone position on the measurement accuracy is very small. When smartphone is not fixed at center of gravity, the maximal relative errors of yaw rates measured by two sensors of smartphone are 0.739 7% and 0.923 8%, respectively. Average absolute error between fused data and INS data is 0.607 7 (°) ·s^-1. Compared with the data measured by two sensors of smartphone, the average absolute error reduces by 34.3% and 50.0%, respectively. The variance of fused data declines and rapidly converges as the number of measurement increases. The convergent time is about 6 s.
- automotive engineering,
- vehicle yaw rate,
- smartphone,
- data fusion,
- self-adaptive weighted algorithm

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References(20)

References

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