The assessment of pavement conditions and their evolution with time is a crucial component for the establishment of pavement quality management (QM) plans and the implementation of QM practices. An effective pavement management system (PMS) is based on pavement conditions data continuously collected along the lifetime of a road. These data are used to model the pavement response, evaluate its performances, and trigger the necessary maintenance actions when they do not meet previously defined performance indicators. In the last decades, pavement monitoring via embedded sensing technologies has attracted more and more attention. Indeed, the integration of sensors in the road pavement allows the assessment of the complete history of pavement conditions, starting from sensor installation. Once the technologies are stabilized, collecting this information is expected to help road managers to define more effective asset management plans. This paper first proposes an overview of the most used devices for pavement instrumentation, categorized according to the measured parameters. Then a review of some prominent instrumented sections is presented by focusing on the methodology used for data interpretation.

Road agencies are constantly being placed in difficult situations when making road maintenance and rehabilitation decisions as a result of diminishing road budgets and mounting environmental concerns for any chosen strategies. This has led practitioners to seek out new alternative and innovative ways of monitoring road conditions and planning maintenance routines. This paper considers the use of innovative piezo-floating gate (PFG) sensors and conventional strain gauges to continuously monitor the pavement condition and subsequently trigger maintenance activities. These technologies can help develop optimized maintenance strategies as opposed to traditional ad-hoc approaches, which often lead to poor decisions for road networks. To determine the environmental friendliness of these approaches, a case study was developed wherein a life cycle assessment (LCA) exercise was carried out. Observations from accelerated pavement testing over a period of three months were used to develop optimized maintenance plans. A base case is used as a guide for comparison to the optimized systems to establish the environmental impacts of changing the maintenance workflows with these approaches. On the basis of the results, the proposed methods have shown that they can, in fact, produce environmental benefits when integrated within the pavement management maintenance system.

Regular and long-term infrastructures monitoring is fundamental for asset management, as it provides information on the actual mechanical conditions and triggers maintenance actions. Several tools are currently used for this purpose, such as embedded sensing devices, deflection measurements and visual inspections. In this paper, we analyse data from a full-scale experiment performed on the accelerated pavement testing (APT) facility of the Université Gustave Eiffel (formerly Ifsttar) during the BioRepavation project. Dvnifferent monitoring data are recorded and compared: strains from asphalt strain gauges (ASGs), deflections from Benkelman beam and Falling Weigh Deflectometer (FWD) and crack development survey. Deflections measurements at the end of the fatigue test were used to inverse calculate the layer moduli of pavement. Based on this model, numerical strains are calculated and compared with sensor measurements. The analyses conducted proved that instrumentation embedded ASGs and temperature probes can be used valuably to assess pavement fatigue.

The road network is one of the major assets in our countries. A proper management is essential to guarantee an adequate quality of life and economic growth. This paper presents the effort undertaken for monitoring of a road section with embedded strain gauges. The experimental site is located in Corbas (close to Lyon, France). A 5 cm-thick wearing course made of BBSG (French acronym for “Béton Bitumineux Semi Grenu”) was placed over a pre-existing road covering an area of 6.4 m × 30 m. The pavement was instrumented with six asphalt strain gauges connected to a data acquisition system called PEGASE. An experimental lab campaign was necessary for the assessment of the exact road stratification. The measurement sessions in the trial section were performed with a known loading truck at different temperatures, speeds, and trajectories. Results show a high sensibility of the measurements to the above-mentioned parameters. The mechanical behaviour of the pavement was assessed in the Viscoroute^© software by using both an elastic and a viscoelastic approach. It emerged that the traditional pavement design approach has some limits in predicting the pavement behaviour at high temperature. Indeed in these conditions, a viscoelastic model that takes into account the mechanic contribution of the interfaces seems to be more appropriate. This research is fruit of a collaboration between Eiffage (European, leader in construction and concessions), LPICM (Laboratoire de physique des interfaces et des couches minces), IFSTTAR (Institut Français des Sciences et Technologies des Transports, de l’Aménagement et des Réseaux), and the University of Nottingham in the framework of the network-wide-training programme of SMARTI ETN (launched in 2017 under the Marie Sklodowska Curie Research Fellowship programme, MSCA).