Combined Safety and Cybersecurity Testing Methodology for Autonomous Driving Algorithms

Combined safety and cybersecurity testing are critical for assessing the reliability and optimisation of autonomous driving (AD) algorithms. However, safety and cybersecurity testing is often conducted in isolation, leading to a lack of evaluation of the complex system-of-system interactions which impact the reliability and optimisation of the AD algorithm. Concurrently, practical limitations of testing include resource usage and time. This paper proposes a methodology for combined safety and cybersecurity testing and applies it to a real-world AV shuttle using digital twin, software-in-the-loop (SiL) simulation and a real-world Autonomous Vehicle (AV) test environment. The results of the safety and cybersecurity tests and feedback from the AD algorithm designers demonstrate that the methodology developed is useful for assessing the reliability and optimisation of an AD algorithm in the development phase. Furthermore, from the observed system-of-system interactions, key relationships such as speed and attack parameters can be used to optimise testing.