Road to Repair (R2R): An Afrocentric Sensor-Based Solution to Enhanced Road Maintenance

Abstract

Potholes are one of the most important issues in African road-networks. They pose a major threat to mobility and, with time, cause accelerated degradation of the underlying road infrastructure as well as extensive vehicle damage. To address the need for improved infrastructure management, an advanced data gathering solution is required. This paper presents one such solution. The pothole detection, classification and logging (PDCL) system is under active development by Sensorit (Pty) Ltd in collaboration with the University of Cape Town (UCT) Radar Remote Sensing Group (RRSG). This system represents the initial step in Sensorit's modular approach to producing fully autonomous vehicles for African markets. In this paper, an overview of the PDCL system is presented and early results are shown. The efficacy of the system's unique combination of active infrared stereo vision and mmWave frequency-modulated continuous-wave (FMCW) radar sensors is explored. Under various experimental conditions, range-Doppler maps (RDMs) produced by the radar were unable to provide meaningful pothole detections. In contrast, processed depth maps produced by the stereo vision system are demonstrated to successfully detect even shallow potholes.