System Design for a Driverless Autonomous Racing Vehicle

The rising popularity of autonomous vehicles has led to the development of driverless racing cars, where the competitive nature of motorsport has the potential to drive innovations in autonomous vehicle technology. The challenge of racing requires the sensors, object detection and vehicle control systems to work together at the highest possible speed and computational efficiency. This paper describes an autonomous driving system for a self-driving racing vehicle application using a modest sensor suite coupled with accessible processing hardware, with an object detection system capable of a frame rate of 25fps, and a mean average precision of 92%. A modelling tool is developed in open-source software for real-time dynamic simulation of the autonomous vehicle and associated sensors, which is fully interchangeable with the real vehicle. The simulator provides performance metrics, which enables accelerated and enhanced quantitative analysis, tuning and optimisation of the autonomous control system algorithms. A design study demonstrates the ability of the simulation to assist in control system parameter tuning - resulting in a 12% reduction in lap time, and an average velocity of 25 km/h - indicating the value of using simulation for the optimisation of multiple parameters in the autonomous control system.