Transportation Research Record: Journal of the Transportation Research Board

Highway agencies commonly use automated pavement data collection techniques to collect pavement surface distress data at the network level. Although an immense amount of data is collected at the network level, agencies realize that there is a lack of understanding of the quality of the data collected. Traditionally, either the overall pavement condition rating or individual distress ratings are used to evaluate the quality of the condition data. However, each measure has its own pros and cons, rendering the use of a single measure inadequate. This paper presents a set of performance measures that highway agencies can use to quantify the quality of the pavement condition data collected and processed. The set of measures consists of (a) the pavement condition rating and hypothesis testing for differences, (b) the percentage cumulative difference in the pavement condition rating over its entire range, and (c) kappa statistics for individual distresses. This set of performance measures can be used to assess the effectiveness of an automated method for the collection of pavement condition data and the effect of sampling on the pavement condition ratings obtained by automated techniques. The effectiveness of an automated technique is assessed by comparison with the findings of benchmark manual visual surveys. The performance measures offer a complete assessment of the effect of sampling on the overall pavement condition rating, its variation over the entire range, and the identification of individual surface distresses.

The prioritization of maintenance activities is commonly applied in pavement maintenance planning. A widely adopted practice is to express maintenance priority in the form of a priority index, computed by means of an empirical mathematical expression. Though convenient to use, empirical mathematical indices often do not have a clear physical meaning and cannot accurately and effectively convey the priority assessment or intention of highway agencies and engineers. In an attempt to overcome this limitation, this study explores the use of an analytic hierarchy process (AHP) for the prioritization of pavement maintenance activities. The main aim is to identify an approach that can reflect the engineering judgment of highway agencies and engineers more closely. Three forms of AHP are examined, namely, the distributive-mode relative AHP, the ideal-mode relative AHP, and the absolute AHP. The applications of the three methods are illustrated by using an example problem, and the results are compared with the priority assessments obtained by a direct assessment method in which the raters make the evaluation by directly comparing all maintenance activities together. The study concludes that the absolute AHP is suitable for the pavement maintenance prioritization process, on the basis of its ability to provide priority assessments for pavement maintenance activities in good agreement with the priority assessments obtained by the direct assessment method and its operational advantage in evaluating a large number of maintenance activities.

The Long-Term Pavement Performance (LTPP) program has collected longitudinal profile data for a wide variety of pavements nationally for almost 20 years. The program is managed by FHWA, which also maintains the LTPP database. The Office of Highway Policy Information, also of FHWA, increased the frequency with which state agencies must perform longitudinal profile testing for the Highway Performance Monitoring System (HPMS) from biannually to annually. This paper looks at the LTPP program data to see if the increased frequency being required for HPMS is justified. All data sets used in the study were from general pavement studies (GPS) with either aggregate base or asphalt-stabilized base. The international roughness index (IRI) and the time between successful data collections were used to plot IRI versus time for each section. A polynomial equation of the form ax² + bx + c was fit for each site, and the polynomial was used to calculate the number of years to a 30-point change in IRI by the use of English units of inches per mile. Plots of the change in IRI versus the time between test events by climatic region were also made. As has been reported by others, the largest contribution to the future IRI is the initial IRI. In all climatic zones, the time required to reach a 30-point increase in the IRI decreased with increasing initial roughness. Straight lines fit through the change in IRI versus time between tests had very low slopes that ranged from 0.0052 to 0.0096 point per day. Even at the maximum slope, it takes 3 years to reach a 10-point change in the IRI, using English units. On the basis of the LTPP program data for GPS flexible pavements nationally, annual testing is not warranted.

A new choice model for corrective road maintenance work based on an economic evaluation of users’ expectations and perceptions about road quality is proposed. Because uncertainty affects human subjective perception processes, the model uses fuzzy sets to deal with this kind of uncertainty. Accordingly, the international roughness index was first fuzzified by combining users’ perceptions about pavement conditions with ranges of speeds for four different categories of rural roads. These fuzzy values were then used to calculate vehicle operating costs and freeflow speed. The latter can be considered a function of the international roughness index and the law enforcement factor. To calculate this factor, a fuzzy inference system was set up. Vehicle operating costs and free-flow speed, as well as the value of time, were then used to calculate the travel cost perceived by users. The model finds, through fuzzy maximization of the difference between perceived travel costs before and after interventions, the best allocation of the available budget for a rural road network. In other words, the results suggest the extent of interventions on specific road sections. An application to a real network shows how the proposed model may be used.

Sustainability is characterized as a three-legged stool supported by economic, environmental, and social considerations. This paper demonstrates the feasibility of integrating environmental performance measures, one aspect of sustainable practices, into asset and pavement management. To illustrate these concepts, a Microsoft Excel workbook-based pavement construction decision support tool named Pavement Life-Cycle Assessment Tool for Environmental and Economic Effects (PaLATE) is introduced. Background information is given on life-cycle assessment (LCA) pavement construction tools. PaLATE product life-cycle and LCA phases are covered, in addition to PaLATE data and data sources. A table describing the data used for environmental calculations is included, and the use of an asphalt emulsion seal and the use of an ultrathin hot-mix asphalt overlay are compared by use of the tool. Special attention is given to recycled materials and environmental measures. Concluding remarks suggest different contexts for potential applications of PaLATE, together with network tools that can be used to meet user needs and applications as well as to address feasibility and cost.

The Guide for Mechanistic–Empirical Design of New and Rehabilitated Pavement Structures [referred to as the Mechanistic–Empirical Pavement Design Guide (MEPDG)] is proposed as an advanced pavement design tool that integrates up-to-date pavement practices. The use of axle load spectra instead of the equivalent single-axle load is a dramatic change. However, the collection of an adequate amount of data over years is required for the accurate characterization of future traffic for design; this gives primary importance to pavement designers having a good understanding of the axle load spectra. This paper presents the typical truck load spectra that satisfy the MEPDG requirements for the Washington State Department of Transportation (WSDOT) and that were developed on the basis of the data collected from selected WSDOT weigh-in-motion stations. Sensitivity analysis was conducted with various typical design parameters of WSDOT flexible pavements. The significant findings are that (a) one type of axle load spectrum can present load characteristics for WSDOT in MEPDG, (b) MEPDG is moderately sensitive to the axle load spectra for typical WSDOT pavement designs, and (c) WSDOT needs to calibrate MEPDG before use. The results have been verified in the calibration of the flexible pavement distress models for WSDOT. It is recommended that agencies that lack data resources test and use the default MEPDG axle load spectral inputs and that the bias may be corrected through model calibration efforts.

This paper presents a new formulation and solution to the problem of managing infrastructure-specific, network-level performance goals through the planning of maintenance and rehabilitation (M&R) activities for the case of pavement infrastructure systems. The proposed approach is based on tracking agency-set targets with the use of optimal control theory. In particular, the problem is formulated as a discrete-time, continuous-state-space quadratic linear tracking control problem considering M&R actions for a finite planning horizon. The formulation builds on previous research efforts by using deterministic, yet realistic, empirical deterioration models. The problem is subsequently solved by using a standard nonlinear mathematical programming solver. The results obtained are realistic, and the formulation provides ample modeling flexibility, which allows the decision maker to obtain target-specific optimal solutions.

With the growing need to maintain roadway systems despite increasing competition for resources while ensuring safety and comfort for travelers, sound network-level decision making becomes more vital than ever. A stochastic process known as the Markov chain has been used extensively to capture the uncertainty associated with pavement performance over time and to support this critical decision-making process. By application of the Markov chain, this paper investigates the crack histories of flexible pavements to gain insight into the impacts of two primary factors that contribute to the rapid deterioration of surface cracks in flexible pavements: excessive traffic loading and delayed maintenance and rehabilitation. The empirical results of the investigation, obtained by using the data from the Florida Department of Transportation's pavement condition survey database, are presented. The results show that the impacts of the two factors mentioned above are statistically different from one another in terms of the rate of deterioration of Florida's pavements because of cracks. These findings will assist highway authorities in making more timely and efficient network-level decisions.

Researchers and practitioners have long recognized the advantages of mechanistic modeling. As agencies implement the Guide for Mechanistic–Empirical Design of New and Rehabilitated Pavement Structures [referred to as the Mechanistic–Empirical Pavement Design Guide (MEPDG)] in the local project-level pavement management system (PMS), its potential as a planning tool in network-level analyses remains unrecognized. A unique, large-scale application of MEPDG is presented. The Nebraska Department of Roads uses a decision tree that systematically screens and identifies candidates for entry into a multiyear optimization program. The process uses linear deterioration rates that have been shown to provide an R² value as low as 14%. In a retroactive 5-year analysis, 86 sections were prescreened by using the existing models. Predictions indicated that 85 of the 86 sections would have been candidates for maintenance in the first 5 years, whereas field data suggested that only 23 should have been targeted. Calibrated MEPDG distress models calculated with local performance indices replaced the existing linear models. When the analysis was repeated with the mechanistic–empirical models, 35 of the 86 sections qualified for entry into the 5-year analysis, a 70% improvement in the accuracy of the forecasted cost. This research fulfills a timely need for the transitioning of network-level PMS toward mechanistic practices. Consideration of fundamental material properties, climatic conditions, and the structural response to traffic loading provides improved accuracy in planning. Furthermore, production variability and prediction uncertainties can be quantified and used as an additional probabilistic decision-making parameter. Detailed results of the implementation of MEPDG in the local network-level PMS are presented.

Escalating construction costs caused by increasing crude oil prices have a serious impact on long-term pavement performance. There is an urgent need for transportation agencies to quantify the impact of the long-term loss of pavement performance (LOPP) and the additional pavement preservation need. This paper proposes a mathematical model that can be used to quantify LOPP. Historical data from the Georgia Department of Transportation (GDOT) from fiscal years (FYs) 1999 to 2007, including pavement survey data and resurfacing expenditures, were used to develop Markovian transition probability matrices. The average annual escalation rate (AAER), 18.1%, was obtained by analyzing the historical resurfacing costs. The impacts of different AAERs (15%, 20%, 30%, and 40%) were analyzed. At GDOT's current funding level, the results show that the composite rating of the non-Interstate pavement network with a 40% AAER would drop to 70 almost 2 years earlier than the one with a 15% AAER. If the AAER is increased from 15% to 30%, the pavement preservation cost needed to meet the expected pavement condition triples from $1.1 billion to $3.4 billion. The LOPP that would occur if there were a sudden increase in construction costs (50%, 100%, and 150%) within a single year was also analyzed. The results showed a 7.8% LOPP for a 100% sudden increase in construction costs in FY 2009. With the impact quantified, it is hoped that transportation agencies can communicate with their state legislatures and stakeholders more transparently about their actual funding needs because of escalating construction costs. Finally, recommendations on improving the accuracy of forecasting are also discussed.

Engineers are being challenged to make critical decisions in response to crisis situations occurring around the globe on a seemingly daily basis. The nature of these crises varies widely and can include military missions as well as humanitarian operations in response to hurricanes, tsunamis, fires, and earthquakes. With thousands of lives hanging in the balance, timely and successful responses to these emergencies often depend on the optimal use of the existing horizontal infrastructure, such as roads, airfields, and railroads, in the affected area. Engineers must provide solutions quickly on the basis of limited data, particularly for unanticipated emergency situations. For military operations, options and alternatives are imperative to the success of a mission. This paper describes an analytical approach to the management of uncertainty because of limited data that provides a solution based on seasonal variability in material strengths, spatial variability in material strengths, and spatial variability in pavement layer thicknesses. An example scenario for an airfield is presented to illustrate techniques for analysis of the structural capacity of pavements of marginal quality and quantification of the uncertainty of the results.

During the past decade, considerable efforts have been made to valuate the benefits of investments in rural roads in developing countries. Although the outputs of those studies have led to a global rethinking of traditional road appraisal methods, limited attempts have been made to integrate these findings into the rural road management process. The problem that arises from the analysis is a missing link between the appraisal of the socioeconomic impact and the management of rural roads. The main objective of the present study was to develop a methodology that combined all key aspects required for the sustainable management of rural roads in developing countries. For this, social, technical, economic, political, and sustainability aspects must be considered at the different levels of the management process. A case study developed in Chile is presented to illustrate the application of the proposed framework at the strategic and the network levels. From the application it was concluded that it was possible to combine in a practical and integrated tool all key factors affecting the process of management of rural roads in developing countries.

One of the headline objectives of the U.K. Highways Agency (HA) is to reduce congestion and improve road safety while undertaking necessary highway maintenance. To this end, HA has invested significant resources in developing an appropriate technology to collect road condition and structural data at traffic speeds. This is reflected in the recent procurement for HA of a prototype traffic-speed deflectometer (TSD). The machine, originally developed by Greenwood Engineering A/S of Denmark, exploits the Doppler effect by using lasers to measure pavement deflection velocities under the loaded wheel of a truck. As part of a research program at the U.K. Transport Research Laboratory, the TSD is being developed to undertake structural surveys at traffic speeds. This paper describes the operation of the TSD and continues with a discussion of one of the most challenging aspects of the research program: the development of a calibration procedure. The proposed procedure compares the response of a particular section of road to the TSD, as recorded by an accelerometer embedded in the road pavement, with that recorded by the Doppler lasers on the TSD.

As part of the evaluation of the potential use of the international friction index as the standard for the reporting of friction measurements, the Florida Department of Transportation (FDOT) conducted an assessment of the precision of the dynamic friction tester (DFT) and circular track meter (CTM) test methods. The FDOT CTM equipment and DFT equipment were compared with similar portable equipment owned and operated by the National Center for Asphalt Technology (NCAT) in an attempt to quantify both the repeatability and the reproducibility of the test data obtained. The FDOT portable equipment was mobilized to Auburn, Alabama, for side-by-side testing with the NCAT equipment. This paper summarizes the results of an assessment of the precision of the DFT and CTM equipment on 10 different test surfaces at the NCAT Pavement Test Track. Tests with DFT and CTM were performed at five different locations within each of the 10 different test sections by using both NCAT and FDOT equipment. On the basis of the results of this comparison testing, proposed precision statements are presented for both the repeatability and the reproducibility of the data for the respective pieces of equipment. Correlation relationships are also presented for the portable equipment and the full-scale equipment currently used by FDOT and others.

In 2006, the Ministry of Transportation of Ontario, Canada (MTO), completed a study with the Centre for Pavement and Transportation Technology at the University of Waterloo to evaluate the performance of automated and semiautomated technologies that collect pavement distress data. From that study it was recommended that MTO define concise guidelines for surveying pavement distresses at the network level by using automated collection technologies and semiautomated distress analysis and for the guidelines to give special attention to quality assurance. In light of that recommendation, the study detailed in this paper presents the development of pavement distress guidelines and a distress manifestation index (DMI) for network-level (DMI_NL) evaluations by using automated collection technologies and semiautomated distress analysis. To define and validate DMI_NL, sections evaluated in the previous study were considered. The relative effect of each distress was obtained by linear regression and statistical analysis. The principle used to define the weighting factors was that the distresses considered by the new guidelines should quantify with a minimum error the DMI estimated by the MTO traditional method.