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dc.contributor.authorYang, Xinyi
dc.contributor.authorHu, Liuqing
dc.contributor.authorAhmed, Hafiz Usman
dc.contributor.authorBridgelall, Raj
dc.contributor.authorHuang, Ying
dc.description.abstractTransportation agencies report that millions of crashes are caused by poor road conditions every year, which makes the localization of roadway anomalies extremely important. Common methods of road condition evaluation require special types of equipment that are usually expensive and time-consuming. Therefore, the use of smartphones has become a potential alternative. However, differences in the sensitivity of their inertial sensors and their sample rate can result in measurement inconsistencies. This study validated those inconsistencies by using three different types of smartphones to collect data from the traversal of both a paved and an unpaved road. Three calibration methods were used including the reference-mean, reference-maximum, and reference-road-type methods. Statistical testing under identical conditions of device mounting using the same vehicle revealed that the roughness indices derived from each device and road type are normally distributed with unequal means. Consequently, applying a calibration coefficient to equalize the means of the distributions of roughness indices produced from any device using the reference mean method resulted in consistent measurements for both road types.en_US
dc.rightsIn copyright. Permission to make this version available has been granted by the author and publisher.
dc.titleCalibration of Smartphone Sensors to Evaluate the Ride Quality of Paved and Unpaved Roadsen_US
dc.typeArticleen_US
dc.typePreprinten_US
dc.descriptionRaj 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.accessioned2021-08-02T21:02:11Z
dc.date.available2021-08-02T21:02:11Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/10365/31970
dc.subjectRoad roughness.en_US
dc.subjectRoad Impact Factor.en_US
dc.subjectNoise reduction.en_US
dc.subjectCalibration methods.en_US
dc.subjectMargin of error.en_US
dc.identifier.orcid0000-0002-9020-7261
dc.identifier.orcid0000-0001-5864-2952
dc.identifier.orcid0000-0002-7874-6123
dc.identifier.orcid0000-0003-3743-6652
dc.identifier.orcid0000-0003-4119-9522
dc.identifier.citationYang, Xinyi, Liuqing Hu, Hafiz Usman Ahmed, Raj Bridgelall, and Ying Huang. "Calibration of Smartphone Sensors to Evaluate the Ride Quality of Paved and Unpaved Roads." International Journal of Pavement Engineering, DOI:10.1080/10298436.2020.1809659, August 25, 2020.en_US
dc.description.sponsorshipU.S. Department of Transportation (USDOT), Research and Innovative Technology Administration (RITA), under the agreement of No. 69A3551747108 through MPC project No. 547.en_US
dc.description.urihttps://www.ugpti.org/about/staff/viewbio.php?id=79
dc.language.isoen_USen_US
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.contributor.organizationUpper Great Plains Transportation Institute
ndsu.collegeCollege of Business
ndsu.collegeCollege of Engineering
ndsu.departmentTransportation and Logistics
ndsu.departmentCivil & Environmental Engineering
dc.identifier.doi10.1080/10298436.2020.1809659


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