Design and development of an Autonomous Self-Driving RC Car for the Emirates Robotics Competition in 2023: with emphasis on Hardware and Software

An ongoing challenge encountered by contemporary engineering educators pertains to the effective cultivation of students’ enthusiasm towards the fields of science and engineering. One of the most effective strategies to address this challenge involves the implementation of a technological competition that encompasses elements of publicity, technology, and student engagement. This study investigates the construction of an autonomous self-driving 1/10th scale remote-controlled car. The objective of the project was to actively engage in and emerge victorious in the Emirates Robotics Competition of 2023, while enabling the research into suitable technologies for its uses in urban autonomous vehicles. The RC car platform implemented in this study utilizes the Waveshare JetRacer Pro AI Kit B, which is built upon the NVIDIA Jetson Nano platform. The RC car platform underwent customization in accordance with the specific requirements of the competition, resulting in its ability to execute rapid and secure maneuvers. Autonomous driving systems encompass a range of essential functions, including obstacle detection, traffic sign detection, road following, and vehicle control. These functions are achieved through the integration of various pre-existing algorithms that have been appropriately modified to meet the specific requirements of autonomous driving. This paper presents a comprehensive analysis of the hardware and software components of the RC car, as well as an in-depth examination of the deep learning architecture and effective modifications made to the existing algorithms, which will serve grounds for better navigation in live environments that modern vehicles are subjected daily.