Research on Pavement Traffic Load State Perception Based on the Piezoelectric Effect

• Published in: IEEE transactions on intelligent transportation systems Vol. 24; no. 8; pp. 1 - 15
• Main Authors: Jiang, Wei, Li, Pengfei, Sha, Aimin, Li, Yupeng, Yuan, Dongdong, Xiao, Jingjing, Xing, Chengwei
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-08-2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Asphalt mixes; Highway construction; Information management; Laboratory tests; Loads (forces); Mathematical analysis; Parameters; Pavement perception; Pavements; Perception; perception accuracy; piezoelectric effect; Piezoelectricity; Sensors; Shafts (machine elements); traffic load state; Traffic speed
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2023.3264248

Accurate multi-parameter perception of pavement traffic load state is a prerequisite for smart highway construction, which is essential in improving the level of road intelligence and realising road information management. This research was based on the piezoelectric effect. Piezoelectric perception devices and strips were prepared and placed in asphalt mixture specimens and test sections, respectively. Through laboratory tests and outdoor vehicle loading tests, piezoelectric signals were collected by the data collector. The signal output peak value, peak area, and other parameters of piezoelectric sensing devices under different test conditions were analyzed. The perceptive calculation method of driving speed, axle number, wheelbase, and total vehicle weight was proposed. The perceptual calculation formula of vehicle load, including temperature, vehicle speed, and signal output parameters, was established and improved. The results show that the peak value of the output signal has a high correlation with test temperature, load, and loading frequency. Also, the signal of piezoelectric material under wheel loading has good stability; the perception accuracy of driving speed can reach more than 95%, the perception accuracy of vehicle axle number was 97.3%, the perception accuracy of vehicle wheelbase was 92.99%, and the perception accuracy of total vehicle weight was 95.19%. Piezoelectric devices have high accuracy in the perception of traffic load state.