Stereo Vision Based Pothole Detection System for Improved Ride Quality

Stereo vision based sensing systems have gained significant attention during the last two decades due to its reliable and accurate obstacle detection and recognition capabilities. Such systems with advanced processing units are now widely used in partially automated vehicles to improve passengers’ safety and comfort level. A predictive suspension control system that could provide better ride comfort and safety to the passengers by detecting potholes in advance and control the suspension system accordingly has been investigated in this study. Potholes can become serious safety hazard and can often cause discomfort if not detected and maneuvered at the right time. In this paper, a novel stereo vision based pothole detection system is proposed that detects pothole and calculates its depth accurately. In this proposed system, region of interest (ROI) of potential pothole candidates are selected utilizing intensity image and disparity image which is created using a pair of stereo images captured by a stereo camera. An intensity-depth based classifier has been developed which identifies the potholes from selected candidates and calculates its depth. Finally, 3D information of detected potholes is used to control the damping coefficient of the suspension system to improve the ride quality. The performance of the proposed pothole detection system has been evaluated using approximately 3.5 hours of driving video data captured with a frame rate of 20 frames/second. Experimental results show that, the accuracy of the proposed pothole detection system is about 84% and can detect pothole with ≥ 5 cm depth. Moreover, in-vehicle experiments confirm that the ride quality can be improved of about 16% utilizing the pothole detection system. The proposed system can be implemented for real-time applications in commercial vehicles and could provide significant benefits by improving safety and ride quality.