Browsing by Author "Hu, Liuqing"

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Calibrating Smartphones for Monitoring Road Condition on Paved and Unpaved Roads
(North Dakota State University, 2018) Hu, Liuqing
Transportation agencies report the localization of roadway anomalies that could cause serious hazards to the traveling public. However, the high cost and limitations of present technical prevent scaling the road monitoring to all roadways. Especially the unpaved road, because of the complexity of unpaved road. Using smartphone application as road condition data collection tool offer an attractive alternative because of its potential to monitor all roadways in real time and its low cost. However, the sensor sensitivity and sampling frequency of different smartphones may vary significantly, which challenge the confidence of using smartphones for actual pavement condition assessment applications. This study tends to solve this challenge by calibrating different smartphones using two different calibrating methods including calibrating towards reference or average road roughness.
Calibration of Smartphone Sensors to Evaluate the Ride Quality of Paved and Unpaved Roads
(2020) Yang, Xinyi; Hu, Liuqing; Ahmed, Hafiz Usman; Bridgelall, Raj; Huang, Ying; Upper Great Plains Transportation Institute
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.
Effects of smartphone sensor variability in road roughness evaluation
(2021) Ahmed, Hafiz Usman; Hu, Liuqing; Yang, Xinyi; Bridgelall, Raj; Huang, Ying; Upper Great Plains Transportation Institute
Accelerometers embedded in smartphones have become an alternative means of measuring the roughness of roads. However, the differences in their sensitivity and sampling rates between smartphones could produce measurement inconsistencies that challenge the wide spread of the smartphone approach for road roughness measurements. In this study, the roughness measurement inconsistency was investigated between smartphones from three different brands. Using the same vehicle, device mount method, traversal speed, and method of producing a roughness index, field experiments demonstrated that accelerometer sensitivities and maximum sample rates vary significantly among smartphones of the same brand as well as across brands. For each smartphone, to achieve a margin-of-error within a 95% of confidence, significant large amounts of traversals are needed. Specifically, 24 and 35 traversals for a paved and an unpaved road, respectively. A higher sampling rate produced more consistent measurements and the least margin-of-error but resulted in larger data sizes. In addition, the measurements from all smartphones were not very sensitive to the size of the feature extraction window, therefore, selecting the largest practical window size will minimize the data size without significant loss of accuracy. For practical application, calibration is necessary to achieve consistent roughness measurements between various different smartphones.