An Analysis Method of Safety Requirements for Automotive Software Systems

Safety requirements have been critical to the automotive software systems, and various advanced driving assistance systems and automated emergency braking systems have been developed with complex software systems. In this article, we propose a modeling and quantitative analysis method of safety requirements which integrates the safety patterns, extended misuse case analysis and evaluation method based on the Bayesian networks. In automotive software systems, the threats to the safety include not only external factors from outside the automobile, but also internal factors such as a driver's erroneous operation. The proposed method enables to analyze both internal and external factors of the system as the hazards to the safety of the systems. First, we define safety a set of patterns as a pair of a cause and the mitigation use cases in order to prevent hazards. With the safety patterns, we can identify a set of mitigation points. Then, we analyze extended misuse cases, which enables to identify hazards to the system failures, and mitigation use cases from the misuse case scenarios. Finally, with the Bayesian networks, we quantitatively evaluate the effect of safety requirements by comparing the accident probability of before and after the application of mitigation use cases. We applied the propose method to the actual autonomous emergency braking systems of passenger vehicles of different model years, and demonstrated the validity and effectiveness of the method.