Visual Control of Autonomous Vehicle by Neural Networks Using Fuzzy-Supervised Learning
Young-Jae Ryoo, Young‐Cheol Lim · Journal of Electrical Engineering and Information Science · 1997
This paper describes a control scheme for an autonomous vehicle with visual sensors, which uses visual information to guide itself along roadways. The control system integrates visual data into the steering servo process direct]y, instead of subdividing the process by geometric reasoning for a vehicle-centered representation of the road from two-dimensional visual image data. A neural network using fuzzy-supervised learning is used for determining the steering angle required to move the vanishing point and vanishing line of the road to the desired position in the camera image. The validity and the effectiveness of the proposed control scheme are confirmed by a computer simulation of the autonomous vehicle's driving performance.