Risk analysis of software execution in an autonomous driving system
Joanna Ekehult · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2020
Autonomous vehicles have the potential to offer efficient ways of moving and improvethe safety of driving. For this to occur, it must be ensured that the autonomousvehicles have a safe and reliable behaviour in nearly all situations andunder nearly all circumstances. The system that enables autonomy relies on astack of complex software functionalities, where the response and execution timesare hard to predict. It is therefore essential to create effective tools and frameworksfor evaluating the performance of the autonomous driving system in a riskyscenario. The aim of this thesis is to create and evaluate a framework for analysingthe risks of an autonomous driving system. The approach is based on an abstractmodel of the main components and interactions of the autonomous system. It providesa manner for systematically analysing the system’s behaviour through simulationswithout requiring timely and costly testing, or a very detailed and complexmodel. Specifically, the use of the method for analysing the autonomous vehicle’stiming behaviour in a risky scenario is investigated.The developed framework is used to evaluate the ability of a vehicle to stop beforecolliding with a static obstacle. In such scenario, the model-based approach foranalysing the risks for an autonomous system is feasible and effective and canprovide useful information during the development process.