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Proceedings Paper

Evaluating road surface conditions using dynamic tire pressure sensor
Author(s): Yubo Zhao; H. Felix Wu; J. Gregory McDaniel; Ming L. Wang
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Paper Abstract

In order to best prioritize road maintenance, the level of deterioration must be known for all roads in a city’s network. Pavement Condition Index (PCI) and International Roughness Index (IRI) are two standard methods for obtaining this information. However, IRI is substantially easier to measure. Significant time and money could be saved if a method were developed to estimate PCI from IRI. This research introduces a new method to estimate IRI and correlate IRI with PCI. A vehicle-mounted dynamic tire pressure sensor (DTPS) system is used. The DTPS measures the signals generated from the tire/road interaction while driving. The tire/road interaction excites surface waves that travel through the road. DTPS, which is mounted on the tire’s valve stem, measures tire/road interaction by analyzing the pressure change inside the tire due to the road vibration, road geometry and tire wall vibration. The road conditions are sensible to sensors in a similar way to human beings in a car. When driving on a smooth road, tire pressure stays almost constant and there are minimal changes in the DTPS data. When driving on a rough road, DTPS data changes drastically. IRI is estimated from the reconstructed road profile using DTPS data. In order to correlate IRI with PCI, field tests were conducted on roads with known PCI values in the city of Brockton, MA. Results show a high correlation between the estimated IRI values and the known PCI values, which suggests that DTPS-based IRI can provide accurate predictions of PCI.

Paper Details

Date Published: 9 March 2014
PDF: 7 pages
Proc. SPIE 9063, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2014, 90630J (9 March 2014); doi: 10.1117/12.2045902
Show Author Affiliations
Yubo Zhao, Northeastern Univ. (United States)
H. Felix Wu, Univ. of North Texas (United States)
J. Gregory McDaniel, Boston Univ. (United States)
Ming L. Wang, Northeastern Univ. (United States)


Published in SPIE Proceedings Vol. 9063:
Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2014
H. Felix Wu; Tzu-Yang Yu; Andrew L. Gyekenyesi; Peter J. Shull, Editor(s)

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