Identification of Moving Load Characteristic on Pavement Using F-P Cavity Fiber Optical Technology

Cai Zhao, Zeying Bian, Hongduo Zhao, Lukuan Ma, Mu Guo, Kedi Peng and Erli Gao
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Cai Zhao: Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
Zeying Bian: Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
Hongduo Zhao: Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
Lukuan Ma: Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
Mu Guo: Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
Kedi Peng: Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
Erli Gao: Inner Mongolia Transportation Design and Research Institute Co., Ltd., Hohhot 021000, China

Sustainability, 2022, vol. 14, issue 4, 1-14

Abstract: The weigh-in-motion (WIM) system is a necessary piece of equipment for an intelligent road. It can provide real-time vehicle weight and lateral distribution data on wheel load to effectively support pavement structure design and service life analysis for autonomous driving. This paper proposed an enhanced weigh-in-motion sensors system using Fabry–Pérot (F-P) cavity fiber optical technology. Laboratory testing was performed to evaluate the feasibility of the proposed system and field application was conducted as well. The laboratory results show that the traffic loads could be obtained by measuring the center wavelength changes in the embedded F-P Cavity tunable filter. The laboratory results also show that the vehicle load and the number of vehicle axles can be estimated based on the system transfer function between the dynamic loading and the wavelength variation. The field application indicates that the weighting accuracy of the proposed system could reach 94.46% for moving vehicles, and the vehicle passing speed is the potentially relevant factor. The proposed system also has the ability to estimate the number of vehicle axles and the loading position, and the precision could reach 97.1% and 300 mm, respectively.

Keywords: weigh-in-motion (WIM) system; traffic load identification; Fabry–Pérot (F-P) cavity fiber optical (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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