Mr. Yubo Zhao Profile

Yubo Zhao

at Northeastern Univ

SPIE Involvement:

Author

Publications (2)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 9 March 2014 Paper

Evaluating road surface conditions using dynamic tire pressure sensor

Yubo Zhao, H. Felix Wu, J. Gregory McDaniel, Ming Wang

Proceedings Volume 9063, 90630J (2014) https://doi.org/10.1117/12.2045902

KEYWORDS: Roads, IRIS Consortium, Sensors, Time metrology, Signal generators

Read 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.

Proceedings Article | 11 April 2013 Paper

Evaluating road surface conditions using tire generated noise

Yubo Zhao, H. Felix Wu, J. Gregory McDaniel, Ming Wang

Proceedings Volume 8694, 869409 (2013) https://doi.org/10.1117/12.2012269

KEYWORDS: Roads, Acoustics, Cameras, Protactinium, Statistical analysis, Scanning probe lithography, Image processing, Data processing, Global Positioning System, Ear

Read Abstract +

Classifications of road conditions are crucial because officials prioritize road maintenance decisions based on them. Pavement condition index (PCI) surveys are performed manually and used by many cities in the U.S. to evaluate road surface conditions. In this research, a more efficient method is used to detect road surface conditions. This method applies a probabilistic analysis to acoustic pressure data collected from a vehicle-mounted microphone. The data is collected while the driving and processed in real time. Acoustic pressure data contains information on road surface conditions because acoustic pressures change when the tire impacts different road surfaces. This change is audible to human ears, for example, a driver transitions from a normal road to a bridge. The acoustic pressure data used in this research was collected from roads with known PCI values that are used as a reference. To reveal the dominant common features and neglect trivial differences within a certain length of road, a probabilistic method is used to evaluate road surface conditions. This approach uses the Weibull probability density function (PDF) to evaluate road surface conditions. This distribution was chosen because it is closest to the actual PDF among other distributions such as the normal distribution and lognormal distribution. A key finding of this paper is that the Weibull PDF shows the largest change between roads with different PCI values. Another finding is that the Weibull pdf changes when the van hits road defects such as cracks and patches.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years