Road Roughness Detection Based on Discrete Kalman Filter Model with Driving Vibration Data Input
Author:
Funder
the National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Mechanics of Materials,Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42947-023-00359-y.pdf
Reference36 articles.
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2. Jian, M. A., Xiang-mo, Z. H. A. O., Shuan-hai, H. E., Hong-xun, S. O. N. G., Yu, Z. H. A. O., Huan-sheng, S. O. N. G., & Lan, Y. A. N. G. (2017). Review of pavement detection technology. Journal of Traffic and Transportation Engineering, 17(5), 121–137. https://doi.org/10.3969/j.issn.1671-1637.2017.05.012
3. Yu, Q., Fang, Y., & Wix, R. (2022). Pavement roughness index estimation and anomaly detection using smartphones. Automation in Construction, 141, 104409. https://doi.org/10.1016/j.autcon.2022.104409
4. Aleadelat, W., & Ksaibati, K. (2017). Estimation of pavement serviceability index through android-based smartphone application for local roads. Transportation Research Record, 2639(1), 129–135. https://doi.org/10.3141/2639-16
5. Aleadelat, W., Ksaibati, K., Wright, C. H., & Saha, P. (2018). Evaluation of pavement roughness using an android-based smartphone. Journal of Transportation Engineering, Part B: Pavements, 144(3), 04018033. https://doi.org/10.1061/jpeodx.0000058
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