| dc.contributor.author | Zhang, Zhiming | |
| dc.contributor.author | Deng, Fodan | |
| dc.contributor.author | Huang, Ying | |
| dc.contributor.author | Bridgelall, Raj | |
| dc.description.abstract | The international roughness index (IRI) is a characterization of road roughness or ride quality that transportation agencies most often report. The prevalent method of acquiring IRI data requires instrumented vehicles and technicians with specialized training to interpret the results. The extensive labor and high cost requirements associated with the existing approaches limit data collection to at most once per year for portions of the national highway system. Agencies characterize roughness only for some secondary roads but much less frequently, such as once every five years, resulting in outdated roughness information. This research developed a real-time roughness evaluation approach that links the output of durable in-pavement strain sensors to prevailing indices that summarize road roughness. Field experiments validated the high consistency of the approach by showing that it is within 3.3% of relative IRI estimates. After their installation and calibration during road construction, the ruggedized strain sensors will report road roughness continuously. Thus, the solution will provide agencies a real-time roughness monitoring solution over the remaining service life of road assets. | en_US |
| dc.rights | In copyright. Permission to make this version available has been granted by the author and publisher. | |
| dc.title | Road Roughness Evaluation Using In-Pavement Strain Sensors | en_US |
| dc.type | Article | en_US |
| dc.type | Preprint | en_US |
| dc.description | Raj Bridgelall is the program director for the Upper Great Plains Transportation Institute (UGPTI) Center for Surface Mobility Applications & Real-time Simulation environments (SMARTSeSM). | en_US |
| dc.date.accessioned | 2021-08-03T20:34:31Z | |
| dc.date.available | 2021-08-03T20:34:31Z | |
| dc.date.issued | 2015 | |
| dc.identifier.uri | https://hdl.handle.net/10365/31978 | |
| dc.subject | Road roughness. | en_US |
| dc.subject | Ride quality. | en_US |
| dc.subject | In-pavement strain sensors. | en_US |
| dc.subject | Structural health monitoring. | en_US |
| dc.identifier.orcid | 0000-0002-7678-605X | |
| dc.identifier.orcid | 0000-0001-5292-5011 | |
| dc.identifier.orcid | 0000-0003-4119-9522 | |
| dc.identifier.orcid | 0000-0003-3743-6652 | |
| dc.identifier.citation | Zhang, Zhiming, Fodan Deng, Ying Huang, and Raj Bridgelall, "Road Roughness Evaluation Using In-Pavement Strain Sensors," Smart Materials and Structures, 24 (11), DOI:10.1088/0964-1726/24/11/115029, 115029, October 15, 2015. | en_US |
| dc.description.sponsorship | U.S. Department of Transportation (USDOT) UTC grant under MPC agreement DTRT12-G-UTC08 | en_US |
| dc.description.uri | https://www.ugpti.org/about/staff/viewbio.php?id=79 | |
| dc.language.iso | en_US | en_US |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
| dc.contributor.organization | Upper Great Plains Transportation Institute | |
| ndsu.college | College of Business | |
| ndsu.college | College of Engineering | |
| ndsu.department | Transportation and Logistics | |
| ndsu.department | Civil & Environmental Engineering | |
| dc.identifier.doi | 10.1088/0964-1726/24/11/115029 | |
