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Low values of pavement friction increase crash rates. Some agencies such as FHWA and AASHTO have provided guidelines for the management of pavement friction, including the definition of minimum friction thresholds for roadway networks. Additionally, FHWA lists the Benefit-Cost Ratio (BCR) as one of the methodologies that can assist decision makers in the definition of these thresholds. However, there are limited studies that quantified the BCR of establishing minimum friction thresholds. The objective of this paper is to fill this research gap by providing a methodology to quantify the BCR of establishing minimum friction thresholds for roadway networks. Benefits are estimated in terms of the monetary value of crash reductions. Costs are estimated by considering: a) the cost for treating pavement sections, b) the monetary value of travel time delays, and c) the monetary value of road safety risks associated with work zones. The proposed framework was applied to a roadway network of 993 highway sections in Texas. The analysis was performed for Interstate Highways, Urban Freeways, and Arterials and Collectors. The proposed methodology can provide transportation agencies with an analytical tool to effectively estimate the BCR of maintenance policies intended to establish a minimum SN for a roadway network. [ABSTRACT FROM AUTHOR]

Transportation agencies should have the capacity to evaluate the damage caused by oversize and overweight (OS/OW) vehicles in order to develop effective infrastructure management and rehabilitation strategies. In this paper, we discussed how to combine different paradigms that influence pavement performance into a single evaluation methodology by integrating the most available historical data with respect to the characteristics of OS/OW vehicles (i.e. dimension and weight), their origin and destination, permitted routes, frequency of the routes, pavement condition data, and climatic effects. The proposed methodology is then implemented into three case studies to indicate its applicability and practicality. In the case studies, we evaluate the impacts of OS/OW loads on pavements under different scenarios and combinations of the related factors. The corresponding relationships between pavement conditions and passing OS/OW loads are quantified with a well-accepted sigmoidal function. The results also indicate that, at the early age of the road, higher OS/OW loading would bring a faster deterioration rate (e.g. about 6% of the reduction in service life for extreme high OS/OW loading, while only 2.35% for low OS/OW loading). At the end of road life, the reduction trend slows down, nearly above 2% for all OS/OW loading levels. [ABSTRACT FROM AUTHOR]

Highway maintenance and rehabilitation (M&R) planning is a multifaceted decision-making process that requires the consideration of multiple but often conflicting objectives. Traditionally, state highway agencies (SHAs) have focused on maximizing the condition of a pavement network or minimizing agency costs needed to keep the network at an acceptable physical and functional level of service. However, other objectives like minimizing the road user costs and greenhouse gas (GHG) emissions are seldom factored into the M&R decision-making process. In this paper, a mixed integer program that accounts for these three objectives is presented. The proposed model is then implemented on a subset network in Texas consisting of 100 pavement sections. The results demonstrate the Pareto-optimal relationships that exist between the road condition improvements, road user costs, and GHG emissions. Notably, there is a positive relationship between condition score improvements and the observed marginal GHG emissions from the case network implementation. Furthermore, this network's results indicate that GHG emissions from materials and construction contribute to the most significant proportion of the total estimated GHG emissions. The results of the sensitivity analysis confirm the observed trends in the network case examined and provide valuable insights concerning the impact of variability in the budget size. The principal contribution of this study is in providing an approach for highway decision-makers to perform trade-offs in road condition improvements, road user costs, and GHG emissions of alternate pavement M&R programs or policies. [ABSTRACT FROM AUTHOR]

Current materials and construction specifications for pavement preservation treatments are predominantly prescriptive and rarely correlate the initial quality of the treatment to its future performance. As a result, it is difficult for highway agencies to account for the performance lost or gained due to differences between the as-designed treatment and as-constructed treatment. Also, these specifications may not incentivize contractors to focus on factors that affect the treatment's long-term performance. To account for these limitations, this paper provides a simulation-based performance-related specification (PRS) methodology for pavement preservation treatments, with application to thin hot-mix asphalt (HMA) overlays. Through performance prediction models and lifecycle cost analysis, this methodology determines pay factors based on the probability distributions of the total lifecycle costs of the as-designed and as-constructed treatments and the unit bid price. The developed PRS methodology was applied to four Long-Term Pavement Performance sections in Texas, Idaho, Florida, and New Jersey that received thin HMA overlay treatments. These case studies demonstrated the applicability of the developed methodology and provided insights into the relationships between the initial quality of thin HMA overlays and expected pay factors. [ABSTRACT FROM AUTHOR]

The Texas DOT (TXDOT) is concerned about the widening gap between pavement preservation needs and available funding. Thus, the TXDOT Austin district pavement engineer (DPE) has investigated methods to strategically allocate available pavement funding to potential projects that improve the overall performance of the district and Texas highway systems. The primary objective of the study presented in this paper is to develop a network-level project-screening and ranking method that supports the Austin district 4-year pavement-management plan development. The writers developed candidate-project selection and ranking algorithms that evaluated pavement conditions of each project candidate using data contained in the Pavement Management Information System (PMIS) database, incorporated insights from Austin district pavement experts, and implemented the developed method and supporting algorithm. This process previously required weeks to complete, but now requires about 10 min, including data preparation and running the analysis algorithm, which enables the Austin DPE to devote more time and resources to conducting field visits, performing project-level evaluations, and testing candidate projects. The case study results show that the proposed method assisted the DPE in evaluating and prioritizing projects and allocating funds to the right projects at the right time. [ABSTRACT FROM AUTHOR]

Recently, a structural condition index (SCI) was developed for the Texas Department of Transportation as a screening tool to discriminate between pavements that need structural reinforcement from those that do not. For the successful implementation of the SCI concept at the network level, one of the critical issues is to determine the minimum falling weight deflectometer (FWD) testing frequency. The paper discusses how to determine the required FWD testing frequency, or the required FWD test spacing needed for implementing the SCI at the network level. In this study, the risk-based method was employed, where the variance of the SCI at the network level was assessed by randomly selecting a small sample of the pavement sections that were representative of the whole network. Due to the limited number of such sections and the lack of knowledge of underlying distribution of the SCI variances at the network level, the bootstrap method was used to obtain the mean and the confidence intervals on the mean of the SCI variances at the network level. [ABSTRACT FROM AUTHOR]