Enhancing Real-Time Embedded System Education With Self-Driving Car Models

Abstract

The self-driving car has been developing rapidly over the past decade, with increased attention from both academia and industry worldwide. Specialized research labs are equipped with vehicles fully loaded with cutting-edge technologies. Such labs are very expensive and not accessible to students in developing economies. This work proposes using self-driving car models to enhance real-time/embedded system education. We have built two experimental low-cost self-driving robotic systems designed specifically for the classroom within an educational context. Lego Mindstorms and Arduino platforms were used as they both offer vast teaching opportunities based on interdisciplinary project-based learning. The programming languages used are compatible with professional robotic programming languages. The goals of using the proposed models as autonomous cars were, on the one hand, to encourage students to gain hands-on experiences in the field of mobile robotics and, on the other, to teach senior students programming, problem-solving, real-time systems, and embedded systems. The models successfully attracted students and motivated them to be engaged in classroom activities. Using the proposed models, real-world autodrive features exposed to automated vehicles were implemented and validated.