A Framework for the Selection of AI-Based Methods to Support the Development of Passive Vehicle Safety Systems

Abstract

The complexity of new products driven by rising requirements for new generations demands efficient development processes. A pronounced emphasis on artificial intelligence has resulted in a substantial array of methods in multiple application fields. Hence, this work proposes a framework for the systematic categorization and selection of artificial intelligence-based methods enabling the engineers to employ the best method at the best time. The framework is built upon the problem-solving cycle, discussed along, and verified within the industry use case of passive vehicle safety system design.