Design, optimization, and assessment of integrated safety systems (combining active and passive elements) pose considerable challenges. For example, the spectrum of potential situations in the field in which active elements might be triggered is considerably larger than one can achieve under controlled testing conditions.

In this context, it is crucial to evaluate quantitative metrics relating as closely as possible to human risks and benefits, such as avoidance of injuries or reduction of injury severity. The consequences of unnecessary interventions and other side effects on passengers or traffic also need to be quantified. This paper describes a generic approach to assessment of field effectiveness and evaluation of active and integrated safety systems. The approach, based on virtual experiments, is holistic, in that both active and passive safety elements are evaluated using a common metric while seeking the most effective solutions regarding overall improvement of vehicle safety. The complexity of process models and their interactions utilizes an advanced knowledge base. In order to achieve this goal, the whole sequence of events in a hazardous situation is virtually implemented in a tool chain. The tool chain includes stochastic (or “Monte-Carlo”) traffic simulation, generating large samples of accident sequences but also near-misses, as well as detailed, high-resolution crash simulations of resulting accidents. The methods are useful not only for assessment of existing integrated safety designs, but also for comparing different system concepts or optimizing performance within a complex design concept. The potential of this approach is illustrated for several key accident scenarios.