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We develop a risk-averse safety analysis method for stochastic systems ondiscrete infinite time horizons. Our method quantifies the notion of risk for acontrol system in terms of the severity of a harmful random outcome in afraction of the worst cases. In contrast, classical methods quantify risk interms of the probability of a harmful event. Our theoretical arguments arebased on the analysis of a value iteration algorithm on an augmented statespace. We provide conditions to guarantee the existence of an optimal policy onthis space. We illustrate the method numerically using an example from thedomain of stormwater management.

CVaR-based Safety Analysis in the Infinite Time Horizon Setting