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A Non-Contact Overload Identification Method Based on Vehicle Dynamics
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 2, 2019 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
The vehicle overload seriously jeopardizes traffic safety and affects traffic efficiency. At present, the static weighing station and weigh-in-motion station are both relatively fixed, so the detection efficiency is not high and the traffic efficiency is affected; the on-board dynamic weighing equipment is difficult to be popularized because of the problem of being deliberately damaged or not accepted by the purchaser. This paper proposes an efficient, accurate, non-contact vehicle overload identification method which can keep the road unimpeded. The method can detect the vehicle overload by the relative distance (as the characteristic distance) between the dynamic vehicle's marking line and the road surface. First, the dynamics model of the vehicle suspension is set up. Then, the dynamic characteristic distance of the traffic vehicle is detected from the image acquired by the calibrated camera based on computer vision and image recognition technology. The data error caused by the vehicle vibration can be reduced by the filter set up in this paper. Finally, the actual axle load of the vehicle can be obtained combined with the established model, which can be compared with the recorded standard data to detect overload vehicles. In this paper, the real vehicle test was carried out with Dong Feng Aeolus S30. The results show that the characteristic distance identification absolute error and relative error can respectively be controlled within 42.2mm and 3.18%, and the vehicle load identification precision can be 96.0%. The method above can effectively improve the efficiency of the overload identification and has certain guiding significance for maintaining the safety of intelligent transportation.
- Daolin Zhou - Wuhan University of Technology
- Gangfeng Tan - Suizhou-WUT Industry Research Institute
- Yiran Ding - Wuhan University of Technology
- Shimin Yu - Wuhan University of Technology
- Xiaofei Ma - Wuhan University of Technology
- Shuai Wang - Wuhan University of Technology
- Zhenyu Wang - Wuhan University of Technology
CitationZhou, D., Tan, G., Ding, Y., Yu, S. et al., "A Non-Contact Overload Identification Method Based on Vehicle Dynamics," SAE Technical Paper 2019-01-0490, 2019, https://doi.org/10.4271/2019-01-0490.
Data Sets - Support Documents
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- Li, B. and Wang, X., “Highway Overload and Overrun Analysis Based on System Clustering,” Modern Computer (Professional Edition), 2018.
- Yu, Q., “Damage Mode and Mechanism of the Road by Overloaded Vehicles,” Inner Mongolia Science Technology & Economy, 2018.
- Zhang, W., Zhang, Y., Wei, L., Duan, X. et al., “Impact of Vehicle Overload on Road Life,” Journal of Traffic and Transportation Engineering, 2012.
- Faruk, A., Liu, W., Sang, I., Naik, B. et al., “Traffic Volume and Load Data Measurement Using a Portable Weigh in Motion System: A Case Study,” International Journal of Pavement Research & Technology, 2016.
- Kwon, T., “Development of a Weigh-Pad-Based Portable Weigh-In-Motion System,” Rural Highways, 2012.
- Sun, Z., “The Study of Monitor System Research about the Wireless Traffic Network Based on the Self-Load and GPS,” Northeastern University, 2014.
- Chen, D., Gao, S., Gao, Z., and Wei, Q., “Research on Vehicle Weigh in Motion System,” Automobile Technology, 2008.
- Mo, P., Diao, Z., and Dang, X., Design and Calculation of Automotive Suspension Components (China Machine Press).
- Wang, W., Automotive Design (China Machine Press).
- Yu, Z., Automotive Theory (China Machine Press).