Nanosensor technology for road pavements monitoring

The road network is one of the major assets in our countries. The assessment of pavement conditions and their evolution with time is essential for the establishment of cost-effective maintenance plans. In this respect, pavement instrumentation allows remote and continuous monitoring with no traffic disruption. However it remains a major scientific and technological challenge in terms of devices resilience to the harsh road environment as well as of strategies for sensor data interpretation. The overall goal of this thesis is to prove the feasibility of embedded pavement monitoring by demonstrating the exploitability of embedded sensor data to assess road ageing, and by providing a high performance, low intrusiveness technology. We propose, via an accelerated pavement test, a validation of asphalt strain gauges as monitoring method for fatigue prediction in a road pavement. Thus, we further explored the use of embedded sensors for inverse calculation of pavement mechanical conditions via the instrumentation of an existing road with a network of asphalt strain gauges. The same trial section was the environment for a first validation of a novel sensing technology based on the use of nanocarbon-based flexible strain sensors, later tested under an accelerated pavement test. Thereby we demonstrated how the proposed nanotechnology can overcome some of the drawbacks of existing sensing devices in terms of geometry, compatibility with the road environment, and sensitivity.