Road transportation has always been inherent in developing societies, impacting between 10–20% of Gross Domestic Product (GDP). It is responsible for personal mobility (access to services, goods, and leisure), and that is why world economies rely upon the efficient and safe functioning of transportation facilities. Road maintenance is vital since the need for maintenance increases as road infrastructure ages and is based on sustainability, meaning that spending money now saves much more in the future. Furthermore, road maintenance plays a significant role in road safety. However, pavement management is a challenging task because available budgets are limited. Road agencies need to set programming plans for the short term and the long term to select and schedule maintenance and rehabilitation operations. Pavement performance prediction models (PPPMs) are a crucial element in pavement management systems (PMSs), providing the prediction of distresses and, therefore, allowing active and efficient management. This work aims to review the modeling techniques that are commonly used in the development of these models. The pavement deterioration process is stochastic by nature. It requires complex deterministic or probabilistic modeling techniques, which will be presented here, as well as the advantages and disadvantages of each of them. Finally, conclusions will be drawn, and some guidelines to support the development of PPPMs will be proposed.

Flexible pavements and climate are interactive. Pavements are climate sensitive infrastructure, where climate can impact their deterioration rate, subsequent maintenance, and life-cycle costs. Meanwhile, climate mitigation measures are urgently needed to reduce the environmental impacts of pavements and related transportation on the macroclimate and microclimate. Current pavement design and life cycle management practices may need to be modified to adapt to changing climates and to reduce environmental impacts. This paper reports an extensive literature search on qualitative and quantitative pavement research related to climate change in recent years. The topics cover climate stressors, sensitivity of pavement performance to climatic factors, impacts of climate change on pavement systems, and, most importantly, discussions of climate change adaptation, mitigation, and their interactions. This paper is useful for those who aim to understand or research the climate resilience of flexible pavements.

Optimization-based tools have been included in many engineering management systems for individual infrastructure asset classes such as pavement management systems (PMS) and bridge management systems (BMS). These tools typically include single-objective optimization analyses. However, real-world decisions concerning asset preservation and renewal often involve more than one objective reflecting the various goals of the agency and need to evaluate possible alternatives according to multiple criteria. Traditional single-objective optimization approaches for handling such situations optimize a selected most important objective while either neglecting the less important competing objectives or imposing them as known constraints in the optimization formulation. This approach often does not provide truly optimal solutions. Multiobjective optimization formulations have clear theoretical advantages but increase the complexity of the mathematical formulation. This paper presents a review of the application ...

This paper summarizes the research efforts into and applications of the traffic speed deflectometer (TSD) that have occurred over the last 10 years in the United States (U.S.). These are divided into three main topics which are: (1) data analysis methods including data processing, calculation of indices and structural parameters, and temperature correction; (2) evaluation efforts of TSD including repeatability and comparison with the falling weight deflectometer (FWD); and (3) applications of TSD with a focus on flexible pavement management applications, although some efforts on rigid and composite pavements are mentioned. The data analysis methods reviewed are data averaging length and reporting interval, and how deflections are calculated from the measured deflection slopes. For the calculation of indices and structural parameters the following are reviewed: deflection indices that have been proposed, the effective structural number ( SN_eff), and backcalculation of layer moduli. Efforts to evaluate TSD precision (or measurement standard error) are discussed. Then, some comparisons of short-term (time frame of 1 day) and long-term (time frame of 1 year) repeatability of TSD are presented. Compared with FWD, TSD and FWD generally have good correlation, although the measurement principles of the two devices are slightly different. The focus is on network-level applications of TSD, and, more specifically, efforts to include TSD measurements in the pavement management system, especially for flexible pavements applications.

Modelling the pavement deterioration process is essential for a successful pavement management system (PMS). The pavement deterioration process is highly influenced by uncertainties related to data acquisition and condition assessment. This paper presents a novel approach for predicting a pavement deterioration index. The model builds on a negative binomial (NB) regression used to predict pavement deterioration as a function of the pavement age. Network-level pavement condition models were developed for interstate, primary, and secondary pavement road families and were compared with traditional non-linear regression models. The linear empirical Bayesian (LEB) approach was then used to improve the predictions by combining the deterioration estimated by the fitted model and the observed/measured condition recorded in the PMS. The proposed approach can improve the mean square error prediction of the next-year pavement condition by 33%, 36% and 41% for Interstate, Primary, and Secondary roads, respectively, compared with the measured pavement condition without further modelling of the pavement deterioration.

The most common use of reclaimed asphalt pavement (RAP) is in the lower layers of a pavement structure, where it has been proven as a valid substitute for virgin materials. The use of RAP in surface mixes is more limited, since a major concern is that the high-RAP mixes may not perform as well as traditional mixes. To reduce risks or compromised performance, the use of RAP has commonly been controlled by specifications that limit the allowed amount of recycled material in the mixes. However, the ability to include greater quantities of RAP in the surface mix while maintaining a satisfying field performance would result in potential cost savings for the agencies and environmental savings for the public. The main purpose of this research was to produce highly recycled surface mixes capable of performing well in the field, verify the performance-based design procedure, and analyze the results. To produce the mixes, a balanced mix design (BMD) methodology was used and a comparison with traditional mixes, prepared in accordance with the requirements of the Virginia Department of Transportation’s volumetric mix design, was performed. Through the BMD procedure, which featured the indirect tensile cracking test for evaluating cracking resistance and the Asphalt Pavement Analyzer (APA) for evaluating rutting resistance, it was possible to obtain a highly recycled mix (45% RAP) capable of achieving a better overall laboratory performance than traditional mixes designed using volumetric constraints while resulting in a reduction in production cost.