Autonomous systems are often needed to perform tasks in complex and dynamic environments. For this class of systems, traditional safety assuring methods are not satisfying due to the unknown effects of the interacting system with an open environment. Briefly speaking: What is not known during the development phase, can not be adequately considered. In order to realize a more flexible safety analysis, the internal representation of the outside world to be learned by an autonomous Cognitive Technical System, is used to identify hazardous situations. The so-called safety principles represent the hazard knowledge. These can be added to the system prior to operating time without losing the possibility of adjusting or expanding this hazard knowledge during operating time. This contribution details a new method for safety assurance and therefore proposes the introduction of so-called safety principles. Furthermore, the Cognitive Technical System provides anticipation capabilities, so that is becomes possible to expand the planning process in order to take hazard information into account. Finally, a simulation example demonstrates how the autonomous system determines possible future actions, evaluating them with regard to hazards in order to provide a plan with acceptable risk. Nevertheless, the approach can also be implemented to real world applications since typical real world phenomena as uncertainty and faults can also be considered in the chosen virtual world figuratively.