Simulation for Development of Microcomputer Car with White Line Following Controller

The objective of this research is to develop a controller that accurately tracks white lines and propose a control method for white line tracking vehicles using a camera. In this control method, a Convolutional Neural Network (CNN) is applied to the line image, and the control amount is determined based on the class probabilities obtained. To optimize the parameters, Differential Evolution is utilized. When creating the model, the same image is included in multiple classes to introduce ambiguity in the output probabilities and ensure smoother transitions between courses. Furthermore, the generated model is compared with the driving data acquired at the time of image capture to confirm its tracking performance.