For further development of the community, it is necessary to have a functional and high-performance infrastructure which is adapted to the usage requirements. Pavements that are designed concerning the expected loading are the basis for the operability warranty of the road network. The German Guideline for the analytical pavement design process of asphalt pavements (RDO – Asphalt 09) is the basis for an economically and ecologically sustainable design. Using the design process described in the RDO – Asphalt 09 it is possible to consider different factors that influence the loading of an asphalt pavement. Hence, the layer thickness can be set in dependence of the loading.

The two input parameters relevant for the design - traffic loading and temperature conditions - are treated as probabilistic parameters. These two parameter are integrated in the calculation as empirical distributions. In the current German Guideline the procedure for the combination of the temperature conditions and the traffic loading based on the assumption that the both input parameters are stochastically independent. One combination of the temperature conditions, including the frequency of occurrence, corresponds one of many possible load regimes. As a result of the design process, one specific value for the service life of asphalt pavement will be calculated. Different load regimes may lead to differing service life of the asphalt pavement.

As a rule, the true load regime of an asphalt pavement in the future is unknown. Therefore, a new procedure was developed by the authors, with which the combination of the input parameter (temperature conditions and traffic loading), including the frequency of occurrence, are determined quasi randomly. By multiple using this procedure within a design process, the result of the design process of asphalt pavement will be a distribution of service life of this asphalt pavement. This distribution can be statistically evaluated afterwards. The forecasting reliability will be significantly improved by using this model.