Development of a Smartphone Application Serving Pavement Management Engineers

Abstract

Determining the presence and location of pavement defects is vital to the timely maintenance of road infrastructure. Many applications exist for the purpose of tracking user-reported pavement distresses and roadway hazards, but few leverage the capabilities of modern smartphones. This pilot study aims to establish proof of concept that a custom-built smartphone application possesses the ability to utilize onboard smartphone sensors to collect global positioning system (GPS) and vibrational data with accuracy and sensitivity suitable for detecting pavement defects. An application was developed for Android and iOS that utilizes smartphone GPS, accelerometer, and gyroscope sensors to sample and log location, vibrational, and rotational data. The datasets obtained by the application are used to quantitatively establish the application’s ability to detect abnormalities in sampled data when in the presence of pavement defects or abnormal road conditions versus a baseline noise margin under no pavement defects. Additionally, the true sampling frequencies of both platforms are established to compare against user-specified sampling frequencies to determine true sampling performance. Furthermore, the datasets obtained from the Android and iOS platforms are compared to establish that there are differences in sensor hardware used that affect the sensor responses. Results from analysis of the datasets support the conclusion that the application successfully samples smartphone sensors, which can be used to detect defects in pavement when mounted to a vehicle windshield, as well as having the ability to provide relatively accurate and precise location data, given commercial smartphone GPS accuracy limitations.