Yang, XinyiHu, LiuqingAhmed, Hafiz UsmanBridgelall, RajHuang, Ying2021-08-022021-08-022020Yang, 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, 2020.10.1080/10298436.2020.1809659https://hdl.handle.net/10365/31970Raj Bridgelall is the program director for the Upper Great Plains Transportation Institute (UGPTI) Center for Surface Mobility Applications & Real-time Simulation environments (SMARTSeSM).Transportation 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-USIn copyright. Permission to make this version available has been granted by the author and publisher.http://rightsstatements.org/vocab/InC/1.0/Road roughness.Road Impact Factor.Noise reduction.Calibration methods.Margin of error.Article0000-0002-9020-72610000-0001-5864-29520000-0002-7874-61230000-0003-3743-66520000-0003-4119-9522