At Sacyr Concesiones, we are responsible for the operation and maintenance of more than 4,000 km of road infrastructure around the world. That is why it is vital to know the condition of the road surface and be able to anticipate its evolution in order to ensure its proper functioning and maintain high safety standards.
In recent years, we have been developing Apromac, a tool that anticipates how and when a highway's road surface will deteriorate. To do this, it analyzes large amounts of data and uses machine learning to generate predictive models of pavement evolution.
Thanks to our 30 years of experience in highway operation and maintenance, we have been able to provide data on many variables that influence pavement deterioration, such as weather, traffic volume, pavement composition, repair history, etc. Most of this data comes from our P3 highways, such as Rutas del Desierto and Ruta del Limarí in Chile; Turia Highway, Palma-Manacor Highway, Eresma Highway, and Aunor Highway in Spain; and Pirámides-Tulancingo-Pachuca Highway in Mexico, among others.
As a result, Apromac provides predictions about how the main indicators of pavement condition will evolve: the International Roughness Index (IRI), cracking, ruts (depressions in the wheel path), and the Transverse Friction Coefficient (TFC). In addition, it also allows this data to be visualized in graphs and maps with geolocated values.
Once the development of this tool has been completed, the implementation and gradual verification stage will begin. In this way, this tool will help us to plan and execute the necessary pavement upgrades more efficiently, facilitating and improving our work in road operation and maintenance.
This project has been co-financed by the European Union, European Funds, the Ministry of Finance, and CDTI through the Ministry of Science, Innovation, and Universities of Spain.