Research on Camera Rotation Strategies for Active Visual Perception in the Self-Driving Vehicles

Abstract

Aiming at the problem of blind field of view caused by the change in the vehicle’s yaw angle when the self-driving vehicle is turning or changing lanes, this paper proposes a camera rotation strategy based on monocular active environment sensing, which realizes the detection of the blind field of view when the vehicle’s yaw angle changes in the self-driving vehicle. Based on the two-degrees-of-freedom dynamic model, the camera rotation angle control is achieved by controlling the front-wheel angle of the vehicle. A camera control module is designed using Simulink to control the camera in real-time, allowing it to rotate based on different driving scenes. The effect of obstacle detection by traditional vision sensors and active vision sensors is tested under different vehicle driving scenes. The results demonstrate that the obstacle detection effect of the camera rotation strategy based on monocular active environment perception, as designed in this paper, is better than the traditional monocular vision.