Modelling Safety of Autonomous Driving with Semi-Markov Processes

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Abstract: With the advent of autonomous vehicles, the issue of safety-evaluationhas become key. ISO26262 recommends using Markov chains. However, in their most common form, Markov chains lack the flexibility required to model non- exponential probability distributions and systems displaying parallelism. In these cases, generalized semi-Markov processes arebetter suited. Though, these are significantly more taxing to analyze mathematically.  This thesis instead explores the option of simulating these systemsdirectly via MATLAB’s Simulink and Stateflow. An example system, here called CASE, currently under study by Scania was used as an example. The results showed that direct simulation is indeed possible, but the computational times are significantly greater than those from standard MATLAB-functions. The method should therefore be employed on parallel systems when results with a high level of fidelity are needed, and alternative methods are not available. 

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