Pavement preventive maintenance is an important tool for extending the service life of the road pavements. Microwave heating seems to be a promising technology for this application, as bituminous materials have the potential to self-repair above a certain temperature. As ordinary asphalt mixture has low microwave absorbing properties, some additives should be used to improve the heating efficiency. In this paper, the effect of adding Electric Arc Furnace (EAF) slag and Graphene Nanoplatelets (GNPs) on the microwave heating and healing efficiency of asphalt mixtures was evaluated. Microwave heating efficiency was assessed by heating the specimens using several heating times. In addition, the electrical resistivity of the mixtures was measured to understand its possible relationship with the microwave heating process. Furthermore, the healing rates of the asphalt mixtures were assessed by repeated Indirect Tensile Strength (ITS) tests. The results obtained indicate that the additions of graphene and EAF slag can allow important savings, up to 50%, on the energy required to perform a good healing process.

The digitalization of the road transport sector necessitates the exploration of new sensing technologies that are cost-effective, high-performing, and durable. Traditional sensing systems suffer from limitations, including incompatibility with asphalt mixtures and low durability. To address these challenges, the development of self-sensing asphalt pavements has emerged as a promising solution. These pavements are composed of stimuli-responsive materials capable of exhibiting changes in their electrical properties in response to external stimuli such as strain, damage, temperature, and humidity. Self-sensing asphalt pavements have numerous applications, including in relation to structural health monitoring (SHM), traffic monitoring, Digital Twins (DT), and Vehicle-to-Infrastructure Communication (V2I) tools. This paper serves as a foundation for the advancement of self-sensing asphalt pavements by providing a comprehensive review of the underlying principles, the composition of asphalt-based self-sensing materials, laboratory assessment techniques, and the full-scale implementation of this innovative technology.