Risk analysis of software execution in autonomous driving system

Examiner: Karl H. Johansson

Abstract: Autonomous vehicles have the potential to offer efficient ways of moving and improve the safety of driving. For this to occur, it must be ensured that the autonomous vehicles have a safe and reliable behaviour in nearly all situations and under nearly all circumstances. The system that enables autonomy relies on a stack of complex software functionalities, where the response and execution time are hard to predict. It is therefore essential to create effective tools and frameworks for evaluating the performance of the autonomous driving system in a risky scenario. The aim of this thesis is to create and evaluate a framework for analysing the risks of an autonomous driving system. The approach is based on an abstract model of the main components and interactions of the system for driving autonomously. It provides a way of systematically analysing the system’s behaviour through simulations without requiring timely and costly testing, or a very detailed and complex model. Specifically, the use of the method for analysing the autonomous vehicle’s timing behaviour in a risky scenario is investigated. The developed framework is used to evaluate the ability of a vehicle to stop before colliding with a static obstacle. In such scenario, the model-based approach for analysing the risks for an autonomous system is feasible and effective and can provide useful information during the development process.