Despite the increase of population by 4% registered-vehicles by 15% between 2007 and 2010, the number of road-traffic fatalities worldwide remained about the same at 1.24 mil- lion per year [1]. The stagnation of this still remarkable high number suggests that efforts being put into developing road safety measures are actually taking effect and preventing a higher number of road incidents and deaths. Furthermore, the rapid development of novel driver assistance systems, the rising implementation of intelligent traffic infrastructure, and the demographic change worldwide as well as individual performance abilities have had a remarkable effect on driving behaviour and habits. Hence, the classical regularities and models used for traffic research need to be updated. Actual driver and traffic models have a limited capacity to sufficiently illustrate the aforementioned aspects. Only the road users’ reactive behaviour can be taken into consideration; the intervention of assistance systems, an increased amount of information, and the interaction or mutual behaviour adaption of partially assisted traffic participants remain unconsidered. This pushes sim- ulation environments currently being used (driving and traffic simulation) to their limits. Performing efficacy- and safety-tests on future driving assistance or information systems in virtual environments under these conditions is more than questionable, especially in terms of validity. Testing new applications or systems in reality with dummies is costly and time consuming but will be necessary in the future. The interaction between the involved road users is also missing. Moreover, the performance of huge traffic data collections is as- sociated with an immense planning and cost effort. The demand for an effective, efficient tool that supports the activities mentioned is therefore given [2].