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Miniature self-driving cars are intended to facilitate the research and development in the domain of autonomous vehicles. Algorithms developed for the tasks of perception, navigation, and control on such platforms enable fast implementation and testing in scenarios similar to the real world. In this paper, we present a novel methodology for developing the assistance system for a 1/10 scale car, in which we use a simulated GPS to position the vehicle and to navigate on the test track. We propose a method for lane detection and tracking that is robust and accounts for the cases when one or both lines of the lane are missing or not seen in the image. We also present a new solution for detecting road traffic signs. In addition, we have implemented an application for map visualization, that enables us to test the correctness of our algorithms. Our miniature vehicle is capable of successfully navigating from a start point to a goal, while taking into account the lanes, intersections, traffic signs, and can perform lateral parking.
Blaga et al. (Sat,) studied this question.