Model-based design, analysis and assessment framework for safety-critical systems

Safety-critical systems like autonomous driving systems, intelligent robotics and medical surgeon robots, require a stringent dependability while the systems are in operation. Therefore, the safety and reliability issues must be addressed in the development of safety-critical intelligent systems. Nevertheless, the incorporation of the safety/reliability requirements into the system will raise the design complexity apparently. Furthermore, the international safety standards only provide guidelines and lack concrete design methodology and flow. Therefore, developing an effective safety process to assist system engineers in tackling the complexity of the system design and verification, and in the meantime, satisfying the requirements of international safety standard, become an important and valuable research topic. In this study, we will propose a model-based safety-critical system design, analysis and assessment framework which incorporates fault tree-based weak-point analysis, system hardware architecture exploration and safety mechanism effectiveness assessment with model-implemented fault injection. Failure modes and diagnostic coverage analysis (FMEDA) report will be generated after performing the framework. The proposed framework can facilitate the system engineers in designing, assessing and enhancing the safety/robustness of a system with an efficient manner.