01627809

Component

The use of smart phones for pavement roughness evaluation has received considerable attention from researchers. This study focuses on a systematic assessment of several important factors that may affect acceleration-based method. The experimental field tests include factors such as smart phone model, inside vehicle placement, driving speed, proper section length for analysis, section slope, and vehicle model. An APP was developed for data collection, analysis, and transmission to the data center. An inertial profiler and industrial grade accelerometer were used along with the test runs to understand the sensitivity and accuracy of the built-in sensors of smart phones. All factors, except for the section slope, were found to have significant effects on the average root-mean-square acceleration index (ARI) computed from the data obtained from the smart phone. In this study, several ARI normalization procedures were developed to obtain compatible information collected from different smart phone sources. The normalization procedures can be applied directly because most factors, such as driving distance, driving speed, and smart phone model are usually known when data are transmitted to the data center through the APP. Factors, such as vehicle models and smart phone placements are usually unknown when crowdsourcing application is used. However, raw ARI can be normalized through the developed equation, and the relative rough or smooth sections can be identified by each transmitted smart phone.

This paper was sponsored by TRB committee ABJ50 Standing Committee on Information Systems and Technology.

01618707

17-04209

English

10p

2017

Transportation Research Board 96th Annual Meeting

Digital/other

Figures; References

Acceleration (Mechanics); Pavement performance; Roughness; Sensors; Smartphones

Data and Information Technology; Highways; Pavements

Transportation Research Board Annual Meeting 2017 Paper #17-04209

TRIS, TRB, ATRI

Dec 8 2016 11:36AM