Viscoelastic Model for Estimating the International Roughness Index by Smartphone Sensors
This study developed a viscoelastic model that uses smartphone acceleration data to estimate international roughness index (IRI). The developed viscoelastic model is simpler and more straightforward than the majority of previous models that have a similar function. The most notable benefit of the model is that vehicle suspension parameters need not be measured or known. Thirty profile samples from ProVAL 3.5 were selected for model validation. The estimated IRIs from the model showed strong correlations with the IRIs calculated by ProVAL. The proposed model was further verified by comparing the analyzed results of 39 field test sections with the calculated IRIs from ProVAL under two cases, namely, agency application and lack of car information application. In the first case, the suspension parameters were calibrated by least square method using the available field inertial profiler data. In the second case, golden-car parameters were used in the developed viscoelastic model. The IRI linear correlation between the model outputs of these two cases and the ProVAL calculation are R² = 0.91 and 0.89, respectively.
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Supplemental Notes:
- This paper was sponsored by TRB committee AFD90 Standing Committee on Pavement Surface Properties and Vehicle Interaction.
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Corporate Authors:
500 Fifth Street, NW
Washington, DC United States 20001 -
Authors:
- Chen, Chih-Sheng
- Chou, Chia-Pei
- Chen, Ai-Chin
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Conference:
- Transportation Research Board 96th Annual Meeting
- Location: Washington DC, United States
- Date: 2017-1-8 to 2017-1-12
- Date: 2017
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References;
- Pagination: 9p
- Monograph Title: TRB 96th Annual Meeting Compendium of Papers
Subject/Index Terms
- TRT Terms: Acceleration (Mechanics); Roughness; Smartphones; Viscoelasticity
- Identifier Terms: International Roughness Index
- Subject Areas: Data and Information Technology; Highways; Pavements;
Filing Info
- Accession Number: 01627654
- Record Type: Publication
- Report/Paper Numbers: 17-04217
- Files: TRIS, TRB, ATRI
- Created Date: Feb 27 2017 5:12PM