<![CDATA[The development of artificial intelligence science and technology has now begun to penetrate the automotive sector. Autonomous car is one of them that is now starting to take on the role with several capabilities such as lidar sensors, GPS systems, and image reading through the camera. In this paper, an autonomous car uses an image reading system using a camera as an optical sensor. Object detection is needed in real time because the autonomous car continues to move along the track. Researchers use HSV color classification with the Region of Interest method, which has the ability to mark certain areas so that it can be used to optimize system performance to detect and classify trajectories quickly and precisely. This autonomous car uses a 4WD system with a DC motor as the main driver, Raspberry Pi 4 and Arduino nano as the mainboard for operation. The test method in this study includes testing image processing using the Region of Interest, this test includes road detection that has been designed and mechanical testing of the propulsion used in this autonomous car. In this study, trials have been carried out and this prototype successfully works according to the algorithm that has been made. In this trial, the AGV using the ROI method has very accurate reading and movement accuracy. In trials and hardware implementations carried out in this autonomous car laboratory with artificial intelligence, it can work according to the algorithm created with a success rate of 90%.]]>
