Vision-Based Road Segmentation With Active Gaze Control for Autonomous Vehicles

In this article, we aim to enhance the accuracy and usefulness of vision-based road segmentation for autonomous vehicles across various scenarios by actively controlling the gaze of the camera. The camera is mounted on a pan-tilt with two degrees of freedom as azimuth and elevation. The control of the azimuth is a follow-up PID control method mimicking the preview mechanism of human drivers. It is mainly used to improve the usefulness of the road segmentation in turning conditions. The control of the elevation is mainly used to improve the accuracy of the road segmentation in extreme external conditions, at the same time, taking into consideration of the usefulness. The elevation control method is inspired by the saccade-fixation mechanism of human eyes that scans the surrounding environment in the saccade mode and focuses on the object of interesting in the fixation mode. Similarly, the active camera will capture images of the current scene at different candidate elevations and select the optimal elevation. Experimental results demonstrate that the proposed active gaze control method effectively improves the performance of various road segmentation techniques under challenging conditions such as toward-light scenarios, U-turns, and low-speed situations.