Measuring international roughness index (IRI) using several android-based smartphone applications | |
| Author | Emran, Muhammad Al |
| Call Number | AIT Thesis no.TE-20-04 |
| Subject(s) | Smartphones -- Programming Application software--Testing Application software--Performance |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Transportation Engineering |
| Publisher | Asian Institute of Technology |
| Abstract | Immense support towards using smartphone apps for pavement roughness estimations has been increasing day by day due to estimating IRI values quickly, easily, and inexpensively compared to expensive existing roughness measurement approaches. In this study, several Android-based smartphone apps Roadroid, RoadBump, TotalPave, RoadLab, and RoadBounce, are utilized to determine pavement roughness conditions in order to understand the accuracy of those apps. As a part of this confirmatory research, three flexible road sections and three rigid road sections were surveyed, involving a quantitative methodology for collecting the quantitative IRI data using the five apps at realistic vehicle speed using a passenger car. The collected IRI data have been validated with the high-speed inertial profilometer IRI data, which has been collected recently by the local agency Department of Highways, Thailand. Also, compare commercial App(s) and free App(s) to measure IRI and a justification to use of commercial apps. A standard procedure for data collection using apps was recommended by this study and applied to record the roughness data for all smartphone Apps. Quantitative data analysis was done through the graphical analysis using scattered plots with the line of equality, and the inferential statistics compared the group's data points to make inferences by one-way ANOVA test. Two commercial apps Roadroid and TotalPave could provide results similar to the profilometer, but three free apps RoadBump, RoadBounce, and RoadLab, could not provide similar results. All apps bring forth similar results between asphalt and concrete pavements because apps cannot distinguish between asphalt and concrete pavements. Using accurate smartphone Apps can be significantly reduced agency costs regarding roughness estimations. |
| Year | 2021 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Civil and Infrastucture Engineering (DCIE) |
| Academic Program/FoS | Transportation Engineering (TE) |
| Chairperson(s) | Kunnawee Kanitpong |
| Examination Committee(s) | Santoso, Djoen San;Ampol Karoonsoontawong |
| Scholarship Donor(s) | Local Government Engineering Department (LGED), Bangladesh;Asian Institute of Technology Fellowship |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2021 |