A high-performance stereo vision system for obstacle detection

Abstract

Intelligent vehicle research to date has made great progress toward true autonomy. Integrated systems for on-road vehicles, which include road following, headway maintenance, tactical-level planning, avoidance of large obstacles, and inter-vehicle coordination have been demonstrated. One of the weakest points of current automated cars, however, is the lack of a reliable system to detect small obstacles on the road surface. In order to be useful at highway speeds, such a system must be able to detect small (~15cm) obstacles at long ranges (~100m), with a cycle rate of at least 2 Hz. This dissertation presents an obstacle detection system that uses trinocular stereo to detect very small obstacles at long range on highways. The system makes use of the apparent orientation of surfaces in the image in order to determine whether pixels belong to vertical or horizontal surfaces. A simple confidence measure is applied to reject false positives introduced by image noise. The system is capable o...