Integrated recording, innovative forecasting and intuitive mapping of the condition of roads in a digital twinCopyright: © ISAC
In this research project, innovative approaches are to be developed to record the condition of an existing road section (real laboratory) by integrating material and condition data. The generated data will be analyzed automatically using the concept of a digital twin of the real lab in order to develop optimized forecasting approaches for the road condition, with the goal of enabling a more efficient use of resources in road and asset management.
The material and condition data of the real laboratory are to be recorded by means of stationary sensors and Weigh-in-Motion stations. Data from existing sensors will be used, and new sensors will be installed to record the structural condition. In addition, bearing capacity measurements with the falling weight deflectometer and GMO-based laboratory tests on cores taken from the real laboratory are planned.
The digitization of the real laboratory in a digital twin is to be achieved, among other things, by applying 3D photogrammetric methods. For the data exchange or the communication between the sensor or measuring units of the real laboratory and the digital twin, an appropriate data or system design based on application-specific requirements is planned. The database for storing and managing different road graphs and the possibility of referencing all sensor or measurement data to it represents the central element of a digital twin in the field of road superstructure. Within the scope of the research project, tailor-made data storage solutions as well as adapted data entry and data retrieval procedures are to be designed and implemented based on existing database systems. The goal of scalability for the DACH region will be taken into account. For the visualization of the digital twin including the sensor data and the determined results, the advantages and disadvantages of 2.5D, 3D and dashboard views will be analyzed, demonstrated and the most suitable visualization technique will be selected in coordination with the client.
In order to determine the significance and potential of a digital twin for the asset and pavement management of highway operators in the DACH region, systematic research, the analysis of mathematical models and statistical evaluations are to be carried out. Existing models will be processed and compared with more recent developments in order to prepare the models for use in the real laboratory. Based on the developed data and system structure, advanced condition models for relevant damage characteristics of the road pavement will be derived from the collected real-lab data by means of statistical analyses and their information gain will be evaluated. By means of simulations, the effects of optimized measure planning on measure timing and life cycle costs will be presented. In a further step, an investigation of the scaling of the results to the network level and the transferability of the developed approaches to the high-ranking road network in the DACH region will be examined. As an important step in the realization of climate targets on highways and expressways in the DACH region, potentials for the reduction of user costs and emissions in the choice of materials in the context of the optimization of measures will be identified.