Key points are not available for this paper at this time.
Prevailing automotive development focus shifts towards passenger-centric development of vehicle systems. Comparative to autonomous driving development, the challenge evolves to describe all relevant driving situations with the necessary information and context to be able to develop and optimize vehicle systems to actual driving situations. The situational description or scenario, i.e., context or ambiance in which a vehicle is located, represents a fundamental factor in consideration of system behavior and respective system optimization opportunities. The challenge to solve the respective automotive engineering problems for nonlinear multidimensional parameter spaces or mixed integer classification problems is to describe and limit the possible solution space by suitable methodologies. Conventional methods prove inadequate solution as they can only be applied with significant financial resources and engineering time efforts, as known by autonomous driving system development. A key requirement is to reduce the necessity of various concrete scenarios of possible parameter combinations and situation states, in which the vehicle systems operate. We adapt methods to describe driving situations similarly in the context of autonomous driving and derive commonalities for generic application in the context of vehicle development. We discuss our derived and extended approach using two technical case studies from the engineering domains of thermal management as well as energy prediction and point out limitations and pitfalls in application. Conclusively, we present our view on further challenges and opportunities by applying our method in the automotive context and what opportunities arise with our scenario description methodology.
Knödler et al. (Tue,) studied this question.