The challenge faced by national, regional and municipal administrations in the cost- and resource-efficient planning of new construction and maintenance measures on the road network is that the condition of road sections can be assessed primarily on the basis of the surface. The condition of the underlying asphalt layers is usually unknown or can only be roughly estimated.
In order to improve these planning procedures in the future, the German Federal Ministry for Digital and Transport funded the mFUND project "Data-based assessment of the resilience of municipal road infrastructure - DaRkSeit". The aim of the project was to enable the best possible condition monitoring and prediction for the various asphalt layers at the selected study locations with the help of the forecasting method, which is anchored in the German regulations, extensive material tests and measuring stations for temperature and traffic load.
In contrast to the statistical annual distributions for the surface temperature and temperature curves in the construction as well as the traffic load, which are stored in the regulations, the temperatures in the asphalt layers and the axle loads in flowing traffic were measured and evaluated at two measuring stations on a municipal road in the city of Münster. This makes it possible to determine the temperature condition and thus also the material condition for each individual load change. With the help of this information, the resulting damage within the asphalt layers of each vehicle can be calculated and accumulated into a condition value.
The measurement data recorded since December 2022 has shown that the asphalt binder course at a predominantly sunlit position in 2023 fatigued 25% more than that at a predominantly shaded position. It was also determined that the lower temperatures over the course of 2024 caused the asphalt layers to fatigue around 16% less compared to the previous year.
The data at the measuring stations will continue to be collected and will help to predict the remaining service life of the asphalt layers. In addition, the experience gained should lead to similarly precise condition forecasts being made in future for municipal road sections where no permanently installed measurement technology is possible. Finally, the data and simple measurement methods (traffic counts, road surface temperature measurements) will enable a network-wide management system for the road infrastructure.