Journal
SENSORS
Volume 22, Issue 15, Pages -Publisher
MDPI
DOI: 10.3390/s22155756
Keywords
road undulation elevation; data fusion detection; GPS RTK detection; Kalman filtering
Funding
- Shaanxi University of Technology Research Fund: Data fusion road detection system (Talent Initiation Project) [SLGRCQD2022, SLGKY2015]
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This paper introduces a high-speed non-contact vehicle-mounted road undulation elevation detection method, which improves the detection accuracy by combining the advantages of different sensors, and compares the performance of different detection methods.
The detection of long-distance pavement elevation undulation is the main data basis for pavement slope detection and flatness detection, and is also the data source for 3D modeling and quality evaluation of pavement surfaces. The traditional detection method is to use a level and manual coordination to measure; however, the detection accuracy is low and the detection speed is slow. In this paper, the high-speed non-contact vehicle-mounted road undulationelevation detection method is adopted, combined with the advantages of each sensor measurement; three methods are proposed to detect the road undulation elevation: rotary encoders, accelerometers, attitude sensor data fusion detection; GPS RTK detection; and Kalman filtering detection. Through modeling and experimental comparison, Kalman filter detection is not disturbed by the environment, and the detection accuracy is higher than the current international standard.
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