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Right now, the only factor determining when a road needs resurfacing is the condition of the road surface itself. However, the state of the asphalt layer beneath it is also an important marker that has not been adequately taken into account until now. To assess it, only indirect measurement methods are available, which either measure only the surface or damage the road by drilling. A new monitoring system from Fraunhofer researchers and partners detects damage early on and continuously monitors the condition of the underlying asphalt layer, comprehensively and without causing any damage. The centerpiece of the new solution is a fabric of sensors inside the asphalt.
Roads are subject to heavy wear from traffic and environmental factors. Over the long term, these things add up to cracks and other defects in the asphalt. Micro-cracks and damage to deeper layers cannot be detected by the naked eye, however. The current process of assessing the structural condition of the asphalt base layer involves drilling down to take a core sample — a destructive, time-consuming method of measurement that further damages the road and requires road closures. This method is also limited to highly local use. In some cases, this situation produces lengthy and ineffective resurfacing efforts, as the full extent of the damage is often not detected in time.
With all these factors in play, how can the process of planning for road resurfacing be made more sustainable and cost-efficient, with longer-lasting results and less traffic disruption? Researchers at the Fraunhofer Institute for Wood Research, Wilhelm-Klauditz-Institut, WKI have teamed up with partners in the SenAD2 project (see below) to tackle this challenge. They are developing a smart measurement and analysis system that can be used to monitor the condition of the asphalt base layer nondestructively, over a large area and on an ongoing basis, to improve planners’ ability to address road resurfacing. Going forward, the objective is for the system to make it possible to determine and forecast the level of degradation affecting asphalt roads. “Our goal is to be able to plan over a longer period of time, to continuously monitor changes in the condition of the road and, on that basis, to establish forecasts and incorporate them into maintenance management activities,” says Christina Haxter, a research scientist at Fraunhofer WKI. “This won’t make the roads last longer, but it will improve efforts to monitor their condition.”
Supporting fabric made of flax fibers interwoven with electrically conductive wire
The centerpiece of the system is a fabric made of flax fibers and sensor components that is inexpensive to make, so it can be used over large areas. The sensor wire has a diameter of under one millimeter. It is incorporated during the weaving process right into the natural fiber fabric, which is highly resistant to slippage or displacement. Thick, heavy yarns and wide spacing stabilize the material. “The fabric has to be designed in such a way that there is no breakdown of the structure in the asphalt. The sensors must also not be damaged either during the weaving process or when the fabric is inserted into the roadbed,” Haxter explains. On top of that, the fabric has to withstand the weight of trucks and road pavers during construction work. The sensor fabric is produced using a double rapier loom belonging to Fraunhofer WKI. The fabric is produced in a width of 50 centimeters, at any length desired. “The fabric is designed to withstand the rigors of installation and environmental conditions, as our initial tests have shown,” Haxter explains.
Once embedded in the asphalt, the sensor fabric’s job is to provide continuous measurements, allowing for conclusions regarding the internal condition of the asphalt base layer. The stresses that apply to roads create strain on the asphalt base layer, which also causes changes in the condition of the electrically conductive sensors. As the sensor material expands, its electrical resistance also changes. This can be measured, and the change in resistance can be set in relation to the damage to the asphalt base layer or to the road’s condition. The sensor wire is connected to a measurement unit at the side of the road that stores the data and transfers the information to the analysis software.
Effective interaction between digitalization, sensors and AI for road maintenance
Another of the project’s innovations lies in the AI methods used to analyze the data from the asphalt base layer. New calculation methods developed for this purpose determine the current condition of the road surface and also forecast the expected progression of damage. On this basis, the agencies responsible for road construction can initiate necessary road maintenance measures at an early stage and incorporate them into their scheduling and financial planning. The data is visualized using an internet platform with a dashboard that was developed as part of the project. Plans call for using the platform to prepare all of the relevant information and provide it to government agencies, neighbors, businesses, road users and other individuals and entities affected by construction and maintenance work.
Industrial zone tests
After a successful initial series of lab-based feasibility tests, testing is now being performed with a demonstrator on a flat test segment of road in an industrial zone. The sensor fabric has been installed across the full width of the roadbed. Measurement and analysis nodes record the changes in resistance in the sensors when a vehicle travels over the demonstrator.
About SenAD2
Machine learning-based degradation monitoring for asphalt roads
Project funded by:
German Federal Ministry of Transport
Project partners:
• Uhlig & Wehling GmbH Ingenieurgesellschaft (lead entity in the consortium)
• AS+BE Asphalt- und Betonstraßenbau GmbH
• Time4Innovation UG
• Fraunhofer WKI
• Magdeburg-Stendal University of Applied Sciences
• Hochschule Hannover — Hannover University of Applied Sciences and Arts
https://www.fraunhofer.de/en/press/research-news/2025/october-2025/bio-based-fab...
Once embedded in the asphalt, the sensor fabric’s job is to provide continuous measurements, allowin ...
Copyright: © Fraunhofer WKI
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Once embedded in the asphalt, the sensor fabric’s job is to provide continuous measurements, allowin ...
Copyright: © Fraunhofer WKI
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