| dc.contributor.author | Bridgelall, Raj | |
| dc.description.abstract | Rough roads increase vehicle operation and road maintenance costs. Consequently, transportation agencies spend a
significant portion of their budgets on ride-quality characterization to forecast maintenance needs. The ubiquity of
smartphones and social media, and the emergence of a connected vehicle environment present lucrative opportunities for
cost-reduction and continuous, network-wide, ride-quality characterization. However, there is a lack of models to
transform inertial and position information from voluminous data flows into indices that transportation agencies
currently use. This work expands on theories of the Road Impact Factor introduced in previous research. The index
characterizes road roughness by aggregating connected vehicle data and reporting roughness in direct proportion to the
International Roughness Index. Their theoretical relationships are developed, and a case study is presented to compare
the relative data quality from an inertial profiler and a regular passenger vehicle. Results demonstrate that the approach is
a viable alternative to existing models that require substantially more resources and provide less network coverage. One
significant benefit of the participatory sensing approach is that transportation agencies can monitor all network facilities
continuously to locate distress symptoms, such as frost heaves, that appear and disappear between ride assessment
cycles. Another benefit of the approach is continuous monitoring of all high-risk intersections such as rail grade
crossings to better understand the relationship between ride-quality and traffic safety. | en_US |
| dc.rights | In copyright. Permission to make this version available has been granted by the author and publisher. | |
| dc.title | A Participatory Sensing Approach to Characterize Ride Quality | 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 | 2017-12-06T15:15:38Z | |
| dc.date.available | 2017-12-06T15:15:38Z | |
| dc.date.issued | 2014 | |
| dc.identifier.uri | https://hdl.handle.net/10365/26999 | |
| dc.subject.lcsh | Transportation. | en_US |
| dc.subject.lcsh | Accelerometers. | en_US |
| dc.subject.lcsh | Pavements. | en_US |
| dc.identifier.orcid | 0000-0003-3743-6652 | |
| dc.identifier.citation | Bridgelall, R., "A participatory sensing approach to characterize ride quality," Proc. SPIE 9061, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, 90610A, San Diego, CA, March 8, 2014. | en_US |
| dc.description.sponsorship | U.S. Department of Transportation (USDOT) | en_US |
| dc.description.sponsorship | Research and Innovative Technology Administration (RITA) under the Rural Transportation Research Initiative | 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.department | Transportation and Logistics | |
