Bayesian Network Analysis of Safety of Intended Functionality of System Designs

A system comprising a processor configured to:

• calculate, based on safety goals for a functional architecture of an automotive system, nominal requirements for the functional architecture given a particular use case;
• qualitatively determine possible violations to the nominal requirements;
• determine a respective probability of occurrence for at least some of the possible violations;
• construct a Bayesian network including multiple nodes with one or more directed edges, each node of the multiple nodes having a conditional probability derived from the respective probabilities of occurrence determined for the at least some of the possible violations;
• resolve at least one conditional probability table in the Bayesian network by estimating any unknown probabilities in the conditional probability table;
• and
• performing inference with the Bayesian network to estimate a hazard-rate-of-occurrence for the functional architecture in the particular use case.

A system comprising:

• means for defining, for a functional architecture of an automotive system, a target hazard-rate-of-occurrence that satisfies a safety-of-the-intended-function standard for a particular use case;
• means for determining each triggering condition that can occur during the particular use case and a respective probability of occurrence for each triggering condition that can occur during the particular use case;
• means for identifying, based on each triggering condition that can occur during the particular use case, possible hazards to the functional architecture during the particular use case;
• means for identifying, based on the possible hazards, safety goals for the functional architecture;
• means for calculating based on the safety goals, nominal requirements for the functional architecture;
• means for qualitatively determining possible violations to the nominal requirements;
• means for determining a respective probability of occurrence for all but at least one possible violation from the possible violations;
• means for constructing a Bayesian network including multiple nodes with one or more directed edges conveying information between parent and child nodes, each of the multiple nodes having a conditional probability table including the respective probabilities of occurrence for all but at least one possible violation from the possible violations;
• means for resolving each respective conditional probability table in the Bayesian network using a parameter learning algorithm to determine a respective probability of occurrence and deviation in the respective probability of occurrence for at least one possible deviation from the possible deviations;
• means for performing inference with the Bayesian network to estimate a hazard-rate-of-occurrence and a deviation in the hazard-rate-of-occurrence for the functional architecture;
• and
• means for determining changes to the functional architecture that cause the hazard-rate-of-occurrence or the deviation in the hazard-rate-of-occurrence to satisfy the target hazard-rate-of-occurrence.