Izvorni znanstveni članak

https://doi.org/10.17559/TV-20260404003512

The Model of Road Roughness Detection Based on Smartphones and its Application

Jia Wei ; Shaanxi University of Science and Technology, No. 43 Taihua North Road, Weiyang District, Shaanxi Province, China
Xiaolong Zou ; Xi'an University of Science and Technology No. 58 Yanta Middle Road, Beilin District, Xi'an City, Shaanxi Province, China *
Yujing Zhang ; Xi'an University of Science and Technology No. 58 Yanta Middle Road, Beilin District, Xi'an City, Shaanxi Province, China
Jiayue Sun ; Xi'an University of Science and Technology No. 58 Yanta Middle Road, Beilin District, Xi'an City, Shaanxi Province, China
Weixiang Wang ; The Fifth Company of China Railway First Group, No. 58 Yanta Middle Road, Beilin District, Xi'an City, Shaanxi Province, China
Hongjun Jing ; Xi'an University of Science and Technology, No. 58 Yanta Middle Road, Beilin District, Xi'an City, Shaanxi Province, China

* Dopisni autor.

Sažetak

Given the high cost, long detection cycle, and poor universality of traditional road roughness detection methods and the lack of mature models in the existing smartphone-based detection techniques, a smartphone-based lightweight road roughness detection method was proposed in this study, aiming to achieve low-cost, efficient, and accurate measurement of road roughness. First, longitudinal acceleration data were acquired through a smartphone as the data acquisition terminal on an electric bicycle running at a constant speed, the mean value was then eliminated, and Kalman filtering preprocessing was performed for denoising; second, the maximum gap value was measured using a three-meter straightedge, and the international roughness index (IRI) was calculated as the benchmark data; subsequently, the maximum acceleration most highly correlated with IRI was screened based on the Pearson correlation analysis, and a quadratic function fitting model was established; finally, five-level pavement roughness evaluation criteria were established by analyzing such influencing factors as the installation location of the smartphone, the vehicle speed, and the road conditions, and the modelꞌs effectiveness was verified. The goodness of fit (R²) of the model reached 0.8471, and the relative error on 30 verification road sections was kept within 20%. When applied to Zuitou Village Highway detection in Xiꞌan, the model could accurately distinguish "good" and "intermediate" pavements, highly matching the actual road conditions and their service life. The detection method based on smartphone accelerations, which features a low cost, convenient operation and wide coverage, renders a practical technical path for road roughness detection, especially applicable to the refined maintenance monitoring of low-grade roads like rural highways.

Ključne riječi

acceleration; data preprocessing; international roughness index (IRI); pavement evaluation criteria; road roughness detection; rural highway; smartphone; three-meter straightedge method

Hrčak ID:

348684

URI

https://hrcak.srce.hr/348684

Datum izdavanja:

30.6.2026.

Posjeta: 0 *