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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.

Pavement structures are designed to withstand continuous damage during their design life. Damage starts as soon as the pavement is open to traffic and increases with time. If maintenance activities are not considered in the initial design or considered but not applied during the service life, damage will grow to a point where rehabilitation may be the only and most expensive option left. In order to monitor the evolution of damage and its severity in pavement structures, a novel data compression approach based on cumulative measurements from a piezoelectric sensor is presented in this paper. Specifically, the piezoelectric sensor uses a thin film of polyvinylidene fluoride to sense the energy produced by the micro deformation generated due to the application of traffic loads. Epoxy solution has been used to encapsulate the membrane providing hardness and flexibility to withstand the high-loads and the high-temperatures during construction of the asphalt layer. The piezoelectric sensors have been exposed to three months of loading (approximately 1.0 million loads of 65 kN) at the French Institute of Science and Technology for Transport, Development and Networks (IFSTTAR) fatigue carrousel. Notably, the sensors survived the construction and testing. Reference measurements were made with a commercial conventional strain gauge specifically designed for measurements in hot mix asphalt layers. Results from the carrousel successfully demonstrate that the novel approach can be considered as a good indicator of damage progression, thus alleviating the need to measure strains in pavement for the purpose of damage tracking.

The development of the falling weight deflectometer (FWD) in the late 1970s made it possible to determine quickly the in situ modulus and critical stresses/strains in pavement structures, which are generally considered the most important input for the ‘mechanistic’ part of the mechanistic–empirical pavement design method. In 2015, the newly designed FastFWD was released and provided the opportunity to speed up the testing procedure and overall productivity significantly. The increased rate of loading prompted the current study into the possibility of performing in situ accelerated pavement testing to predict pavement deterioration, and to fill the gap between the heavy vehicle simulator and small-scale laboratory test methods. Numerous experimental sequences and test sites have been initiated since the start of the research; in the last of these, 1·6 million load applications were applied and the dynamic modulus master curve was back-calculated and used to filter out the viscoelastic response of the asphalt layer caused by temperature changes within the material from the repeated loading. Based on the findings of this research, an incremental-recursive fatigue model has been used to predict accurately the reduction in asphalt modulus as a function of any combination of loads and temperatures for a known material.

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