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Water film depth (WFD) is an important factor for road traffic safety because of its direct connection with skid resistance, hydroplaning speed, and the tendency of splash and spray. Increasing the pavement macrotexture reduces WFD. However, existing models for WFD prediction have not been developed on highly textured surfaces such as chip seal. Furthermore, the rainfall intensities used for developing most of these models were relatively low, leaving no or low WFD on chip seal surfaces. To propose a WFD prediction model suitable for highly textured surfaces and to consider the effect of surface material type, an experimental study was conducted with 154 different combinations of mean texture depth (MTD), surface material type, surface slope, drainage length, and rainfall intensity. The tests were carried out on chip seal specimens using a full-scale rainfall simulator. Test results from 1,784 WFD readings indicated that the Gallaway and PAVDRN models were not accurate for highly textured surfaces used in this study with MTD ranging from 0.05 to 0.20 in. Two experimental models were, therefore, proposed to predict the WFD; both models displayed a significantly higher correlation between the measured and predicted WFD compared with the existing models. Furthermore, the eco-friendly rubberized chip seal showed an enhanced drainage capability compared with conventional chip seal, especially in low slopes, because of the hydrophobic nature of crumb rubber versus the hydrophilic character of mineral aggregates. Accordingly, the proposed model incorporated a term to consider the effect of surface material type.

Transportation agencies should measure pavement performance to appropriately strategize road preservation, maintenance, and rehabilitation activities. The international roughness index (IRI), which is a means to quantify pavement roughness, is a primary performance indicator. Many attempts have been made to correlate pavement roughness to other pavement performance parameters. Most existing correlations, however, are based on traditional statistical regression, which requires a hypothesis for the data. In this study, a novel approach was developed to predict asphalt concrete (AC) pavement IRI, utilizing datasets extracted from the Long-Term Pavement Performance (LTPP) database. IRI prediction is categorized by two models: (i) IRI progression over the pavement’s service life without maintenance/rehabilitation and (ii) the drop in IRI after maintenance. The first model utilizes the recurrent neural network algorithm, which deals with time-series data. Therefore, historical traffic data, environmental information, and distress (rutting, fatigue cracking, and transverse cracking) measurements were extracted from the LTPP database. A long short-term memory network was used to solve the vanishing gradient problem. Finally, an optimal model was achieved by setting the sequence length to 2 years. The second model utilizes an artificial neural network algorithm to correlate the impacting factors to the IRI value after maintenance. The impacting factors include maintenance activities; initial (new construction), milled, and overlaid AC thicknesses; as well as IRI value before maintenance activities. Combining the two models allows for the prediction of IRI values over AC pavement’s service life.

An accurate pavement performance forecasting model is essential for transportation agencies to perform pavement maintenance, rehabilitation, and reconstruction (MR&R) in a predictive and cost-effective manner. Although some forecasting methods have been successful in forecasting short-term (e.g., 1–2 year) pavement conditions at either the project level or network level, accurately forecasting long-term (e.g., 3–5 year) pavement conditions at both project level and network level under real-world conditions is still challenging. Thus, the goal of this paper is to propose a two-stage machine learning approach based on long short-term memory (LSTM) to achieve not only the short-term, but also the long-term, forecasting accuracy at both the project level and network level. The proposed method involves LSTM in the first stage and an artificial neural network (ANN) in the second stage, resulting into a two-stage model. The LSTM first learns the pattern of pavement deterioration based on sequential data (e.g., historical pavement conditions). Then, the ANN further learns the impacts of roadway factors (e.g., traffic parameter, pavement surface type, working district) to adjust the final forecasting results. The accuracy of the proposed two-stage model has been compared with baseline machine learning methods in 2016 on a large, statewide Florida dataset at both the project level and network level to demonstrate the superior capability of the proposed method. In addition, the proposed method has been tested further to forecast future (5-year) pavement conditions (2016–2020). Results show a promising forecasting accuracy for both the short-term and long-term in comparison with the ground truth.

The major objective of this research was to develop a multi-distress detection system (MDDS) that is competent in detecting various asphalt pavement functional distresses simultaneously from video images using appropriate artificial intelligence techniques. You Only Look Once Version 4 (YOLOv4), a state-of-the-art objection detection architecture incorporated with transfer learning-based approach was utilized to quantify multiple severity-based distresses obtained from actual pavement condition images. Eighteen distress classes were defined consisting of three levels of severity pertinent to cracking, potholes, and patch deterioration. The customized MDDS algorithm was trained and tested on 1,518 images retrieved from three different datasets. During training, MDDS attained an average loss of 1.5123, and the validation mean average precision was reported to be 87.44% after 7,900 iterations. During the training process, the customized architecture transformed the training images and segmented them into two million images that potentially enhanced the probability of prediction even when the images are spatially transformed. The model detected multiple distresses in the pavement video clip at an average rate of 6.7 frames per second, which makes it suitable for real-time distress detection. It is envisioned that the novel real-time MDDS tested on diverse datasets could be used by roadway agencies to identify and quantify severity-based distress classes during the monitoring process itself, which ultimately reduces the time between data analysis, pavement forensic evaluation, and decision making on maintenance interventions.

Pavement maintenance and rehabilitation (M&R) records are important as they provide documentation that M&R treatment is being performed and completed appropriately. Moreover, the development of pavement performance models relies heavily on the quality of the condition data collected and on the M&R records. However, the history of pavement M&R activities is often missing or unavailable to highway agencies for many reasons. Without accurate M&R records, it is difficult to determine if a condition change between two consecutive inspections is the result of M&R intervention, deterioration, or measurement errors. In this paper, we employed deep-learning networks of a convolutional neural network (CNN) model, a long short-term memory (LSTM) model, and a CNN-LSTM combination model to automatically detect if an M&R treatment was applied to a pavement section during a given time period. Unlike conventional analysis methods so far followed, deep-learning techniques do not require any feature extraction. The maximum accuracy obtained for test data is 87.5% using CNN-LSTM.

In a pavement management system (PMS), time to maintenance is generally estimated based on the predicted condition of the pavement. Usually a deterministic approach is applied in the PMS to estimate the time to maintenance by following the deterioration equation of the performance index. However, it is necessary to be aware of the probability of failure to investigate whether the estimated time to maintenance by the deterministic approach is reasonably probable. For this reason, a probabilistic approach is applied in this study to estimate the probability of failure over the estimated time to maintenance. In this approach, the probability of failure is estimated from the distribution of the mean time to maintenance by considering both the overall condition of the pavement and individual instances of distress. These mean times to failure or maintenance are calculated from the overall condition of pavement in relation to the pavement condition index (PCI) when the trigger value becomes 65 or less. A pavement may be expected to fail, however, because of any specific distress before it reaches the PCI trigger value for maintenance. For this reason, the probability of failure of each specific distress is also investigated by using a Monte Carlo simulation. It is found that the survival probability up to the fifth year is approximately 80% to 90% for each category of traffic and material type based on the overall condition, and the probability of failure for individual distress is very low over the performance cycle.

Light pavement rehabilitations and low-cost treatments are extensively employed among transportation agencies on roads with relatively low traffic volumes to optimize available resources. One concern with this approach entails the difficulties of determining the optimal timing for treatment application. Making the best use of limited resources requires improvements in maintenance decision-making for selecting treatments considering all affecting factors and previous experience. This paper presents a machine learning approach in the decision-making process for determining the most appropriate pavement maintenance and rehabilitation alternatives for low-volume paved roads at the network level. Based on regional experts’ recommendations and engineering judgments in Colorado, a wide range of 884 cases of pavement-treatment patterns were generated. Then an artificial neural network (ANN) was trained with pattern-recognition algorithms. Two ANN prediction models were developed on the basis of pavement condition data, represented by six condition indices, and road lengths. The objective of training the models is to evaluate the variability of maintenance practices among five engineering regions within the Colorado Department of Transportation (CDOT). The outcome of this study describes the implementation gaps of pavement-preservation activities among CDOT regions resulting from limited maintenance funding. The regional maintenance selection can be processed by the developed ANN decision-making tool to recommend alternatives from regional recommendations as well as similar applications statewide to fit pavement management needs and expected performance.

Preventive pavement maintenance methods such as slurry seals are cost-effective treatments that increase the longevity of pavements. The incorporation of recycled materials such as reclaimed asphalt pavement (RAP) into asphalt pavement helps to further reduce costs and energy consumption. The present research studied the feasibility of incorporating RAP into slurry seal mixtures or RAP slurry seals. Two slurry seal mixtures containing cement and hydrated lime as fillers were tested. The first mixture comprised slurry seal made with virgin aggregate and the second used RAP as the aggregate. The wet track abrasion test (WTAT) and loaded wheel test (LWT) were conducted to evaluate the performance of the mixtures. Wet cohesion and friction tests (sand patch and British pendulum) were performed on the selected slurry seal mixtures with the best performance under WTAT and LWT. The results show that it is possible to prepare slurry seal containing RAP. Although the curing time relative to the virgin aggregates increased by 1 h for RAP aggregate, the wear value in the WTAT decreased by half. Lateral displacement and the British pendulum test results improved considerably for slurry seals made with RAP aggregates. The results of the sand patch test on WTAT samples showed that slurry seals made with RAP should be lightly rolled after lay-down to improve their friction life. Cost analysis indicates that the use of RAP as an aggregate in slurry seal decreased costs by up to 14%. RAP slurry seal showed better overall performance with lower cost than the virgin slurry seal.

Over the last decade, significant progress has been made to customize the maintenance policies of low-volume roads (LVRs) to local needs and available resources. Low-cost treatments and surface repairs are extensively employed to reduce annual maintenance costs. Colorado Department of Transportation (CDOT) uses chip seals and thin overlays as the available treatment options applied to LVRs. However, the effectiveness of these treatments differs depending on the existing condition of pavements. Some surface treatments and light rehabilitations provide only short-term effectiveness. Multi-year optimization techniques can support decision makers with a set of optimal maintenance activities to achieve specific pavement performance targets. This study applies large-scale optimization to compare the current CDOT maintenance policy with an alternative strategy recommended for low-volume paved roads in Colorado. Genetic algorithms were applied in the optimization models because they are capable of resolving the computational complexity of optimization problems in a timely fashion. The optimized maintenance alternatives were comprehensively investigated for a LVR network in Colorado over a specific planning horizon. The specific optimization constraints and limitations prevailing in LVRs are addressed and introduced in the problem formulation of the optimization process. The results of both performance and cost analysis emphasize the effectiveness of the proposed maintenance strategy compared with the existing one. The alternative policy provides much more benefit-cost saving while preserving the overall pavement performance of the network. This approach is expected to be efficient to quantify the mid- and long-term financial impact of different treatment policies applied to LVRs within modest resources.

The Moving Ahead for Progress in the 21st Century Act highlighted the need to monitor the performance of pavement sections over time. An important aspect of performance monitoring is collecting a statistically significant sample of the network so conclusions can be made about changes in performance and types of maintenance and rehabilitation needed for maintaining these assets. This paper reviews the sampling requirements on the Interstate highway system to draw accurate conclusions about the network. Specifically, the paper answers the following questions: Is two-way data collection necessary? Do data have to be collected in more than one lane in a direction? What is the optimum reporting length? For what percentage of the network should data be collected? Should data be collected annually?

Crack sealing (CS) and crack filling (CF) are commonly used crack treatment methods. However, the study of their performance is still very limited, making it difficult for highway agencies to systematically and optimally select network-level CS-CF projects within available budgets. To address this issue, a generalized performance model for CS-CF–treated pavements is proposed. Detailed crack characteristics—including crack type, density, and width—are employed in the model. In the proposed performance model, crack density related to three types of cracks (transverse cracks, nonwheelpath longitudinal cracks, and wheelpath longitudinal cracks) is used to determine performance gain. Two discount functions are incorporated to consider the negative impact caused by alligator cracks and cracks that are very tight or very wide. The proposed model is instantiated and estimated using the practices of the Georgia Department of Transportation on CS and CF and the department’s pavement distress survey protocol. The case study—which uses three-dimensional laser data collected from a 1-mi pavement section on State Route 26 (US-80) near Savannah, Georgia, from 2011 to 2016—validates the feasibility and reasonableness of the model. An integer programming method is formulated for network-level CS-CF project selection. The testing results of 53 pavement segments show that the model and programming method can be used to select CS-CF projects within budget constraints while maximizing the length-weighted average performance gain. The proposed performance model and integer programming method show promise for use in incorporating CS and CF into a highway agency’s pavement management system. Conclusions and recommendations are offered.

Driver fatigue and drowsiness can have a profound impact on safety. Centerline and shoulder rumble strips are popular countermeasures designed to produce audible and tactile warning when vehicles deviate from the travel lane onto the rumble strips. These warnings reduce the risk of lane departure crashes. Studies show that the noise produced by rumble strips is a function of many variables. Rumble strip depth is known to have the greatest impact in alerting drivers. However, chip seal pavement maintenance operations tend to reduce the original rumble strip design depth, which may have an impact on the functional effectiveness of the rumble strips. The purpose of this study was to conduct a controlled experiment to understand the relationship between milled rumble strip depth and noise and vibration in the vehicle cab. In-vehicle noise and vibration levels were collected on rumble strips of five depths (⅛, ¼, ⅜, ½, and ⅝ in.) and three types (shoulder, single centerline, and double centerline) on three highways in the state of Nebraska by two vehicles traveling at speeds of 45, 55, and 65 mph. Rumble strip depths at ⅛-in. intervals were used to simulate the influence of a chip seal on rumble strip effectiveness. From the in-vehicle sound and vibration levels of all the tested rumble strip depths, it can be hypothesized that a ⅛-in. reduction in the current milled rumble strip design depth, as a result of chip sealing, would not cause a practical reduction in the effectiveness of rumble strips producing audible and tactile warnings to alert drivers.

Maintaining a sufficiently short stopping distance is an important requirement for safe road operation. Stopping sight distances of road sections are decided during the highway alignment and roadway geometric design phase of the road development process. A pavement friction coefficient is used in the calculation of the stopping distances. Since pavement friction coefficient deteriorates with time under traffic action, and the available friction also reduces in wet weather, it is important for pavement maintenance engineers to ensure that sufficient skid resistance is maintained under actual operating conditions so that the stopping distances of road sections are less than the required safe stopping distance. This result requires pavement engineers to monitor regularly the available pavement skid resistance and the corresponding stopping distance of individual road sections. Because skid resistance is an accepted pavement condition to be measured in a pavement management system, it is proposed in this study that braking distance assessment be included as a part of the pavement condition monitoring program of a pavement management system. The proposed procedure consists of two parts: ( a) measurement of skid resistance and evaluation of braking distance and stopping distance and ( b) monitoring of the deterioration trends of individual road sections. The detailed procedure and the analytical tools necessary for the evaluation and prediction of braking and stopping distances, including a finite element skid resistance simulation model, are presented. A numerical example is presented to illustrate the concept and working of the proposed procedure.

Chip seals are applied to existing roadways to slow deterioration and improve pavement surface conditions without increasing the pavement’s structural capacity. The raveling of chip seals can cause damage to vehicles and thus is a safety concern. Raveling resistance is related to both material application rates and material properties. The current chip seal specifications fail to adequately address the material-related aspects of raveling resistance. This study seeks to develop recommendations to address raveling resistance in future chip seal specifications. Strain sweep binder tests, binder bond strength (BBS) tests, and Vialit chip seal mixture tests were conducted to assess early raveling, late raveling, and wet raveling at two intermediate temperatures. The results demonstrate that the bond that develops between the residual binder and the aggregate is highly dependent on the interaction between the emulsion and the aggregate during curing. The importance of emulsion–aggregate compatibility in raveling resistance indicates that raveling resistance cannot be addressed in binder specifications alone. Rather, it is recommended that intermediate temperature raveling resistance should be addressed during chip seal mixture design. Vialit and BBS tests, in which emulsion is cured on rock, can both be used to effectively quantify the aggregate loss potential of a chip seal. These two tests are able to capture the benefits of polymer modification and produce results that correlate. However, the Vialit tests are easier to implement than the BBS tests and require no expensive equipment. Therefore, Vialit tests are recommended to address early, late, and wet raveling resistance in future chip seal specifications.

A project candidate selection and ranking model (PCSRM) is commonly applied in pavement maintenance and rehabilitation planning. Typically, these models use empirical mathematical expressions that do not have a clear physical meaning and cannot accurately assess the priority of transportation agencies or pavement engineers. To overcome this limitation, this study developed a method, based on the analytical hierarchy process (AHP), to identify pavement-related factors and improve the accuracy of the PCSRMs currently used by the Austin District (Texas Department of Transportation) in its 4-year plan. The aim was to identify pavement-related factors that reflected the engineering judgment of transportation agencies and pavement engineers. The proposed method had three major components: AHP design, AHP survey and results analysis, and factors selection. A three-tier hierarchy structure of one objective, five goals, and 18 alternatives was defined. Additionally, a system to check for consistency was developed on the basis of literature recommendations. An Excel-based survey tool was developed with the objective of providing a relatively easy visual interface for the participants. The design and development of the survey tool were carried out in collaboration with the district pavement preservation engineer. Seventeen Texas Department of Transportation pavement experts completed the AHP survey with the required consistency ratio. Clustering analysis was performed to identify the pavement-related factors that showed the highest priorities. The factors with the highest overall weights should be considered in future PCSRM improvement.

An accurate and reliable pavement crack detection system plays an important role in evaluating pavement condition and providing needed information for decision making for pavement maintenance and rehabilitation. Among existing crack detection methods, the seed-based image segmentation method has proved to be fast and efficient for automated crack detection. However, its performance is not stable under varying conditions. This paper proposes an extended and optimized seed-based crack detection method after an extensive review of current practices. The proposed method included two main steps. In the first step, pavement images were preprocessed. Lane marking was masked to be a noncrack area and the nonuniform background of the images was corrected. In the second step, crack seeds were detected through grid cell analysis and then connected through a Euclidean minimum spanning tree construction. In addition, undesirable small objects, such as minimal branches and noises, were removed by a path length–based removal method. The proposed algorithm was evaluated by using 105 pavement images collected with the Texas Department of Transportation VCrack system. The experiment results showed that the proposed method could accurately and efficiently detect cracks in the images.

This paper describes the development of a practical tool for selecting and prioritizing rehabilitation (RH) and preventive maintenance (PM) activities in roadway pavements. The development was based on data collected through a survey of district engineers of the Texas Department of Transportation (DOT). The survey collected data on the key factors used for selecting the projects to be treated and for deciding on RH versus PM treatments: pavement condition and distress scores, average daily traffic, surface age, ride score, and past PM expenditures. Weight factors were developed for each key factor by fitting simple logit curves to data obtained by surveying the 25 Texas DOT districts. These weights were aggregated into a prioritization score for PM treatment and another for RH treatments. This process was implemented into an Excel-based tool. The output of this tool was successfully compared with actual district decisions on the type of treatment applied and the priority assigned to pools of projects.

The objective of this study was to determine whether asphalt rubber (AR) binders will provide similar or better performance compared with a polymer modified asphalt (PMA) binder when used in a high-performance, ultra-thin lift overlay pavement preservation strategy. Current specifications for these types of overlays normally require the use of a PMA binder, because it has the ability to make these overlays more elastic under traffic loading and is less sensitive to temperature fluctuations. However, several state agencies are looking into the feasibility of incorporating sustainable and environmentally friendly technologies, such as AR binders and warm mix asphalt (WMA) technologies, into their asphalt mixtures, including those used for high-performance, ultra-thin lift overlays. This study examined the effect of binder modification type (AR or PMA) and the influence of the use of WMA in high-performance, ultra-thin lift overlays. In general, the mixtures that were tested provided comparable rutting, moisture damage, and low-temperature cracking performance in the high-performance, ultra-thin lift overlay. However, the use of the AR binders indicated reduced performance compared with the PMA binder in mixture fatigue cracking via the beam fatigue test, and mixture reflective cracking in the overlay tester. The results from the beam fatigue test were not always supported by the fatigue life predictions from the simplified viscoelastic continuum damage model. The only detriment to mixture performance for mixtures incorporating WMA was a reduction in fatigue cracking performance when used with AR binders.

Errors in pavement condition data can affect not only the assessment of current and predicted performance of the network but also the quality of pavement maintenance and rehabilitation plans. The large size of pavement condition databases makes manual error detection methods difficult to implement. This paper provides a new computational technique for detecting errors in network-level pavement condition data sets. The technique integrates conventional statistical methods and heuristics. The statistical methods are used to identify outliers in uniform performance families, and the heuristics are used for delineating potential errors from extreme, yet valid, behavior within these outliers. The new technique was validated with field data from Texas on pavement cracking. Of 9,166 audited pavement sections, 681 sections having potentially erroneous cracking data were detected. These potential errors are randomly distributed across the Texas roadway network and are not related to a specific geographic region, district, or climatic zone. Pavement engineers can use the presented technique to identify potential errors in large pavement condition data sets and to design more effective programs that ensure the quality of these data.

Recent military operations have highlighted the need for new expedient pavement repair capabilities to improve current guidance on airfield damage repair. Damaged or distressed military airfield pavements must be repaired with expedient methods and durable materials to minimize the time the pavement is removed from service and to reduce or eliminate additional closure times for subsequent repairs. Extensive research was conducted to develop several airfield pavement repair techniques that could be applied across the full spectrum of military airfield repair operations. This paper focuses on the research conducted to develop a new foam backfill technology for airfield pavement repairs. Results of initial laboratory and field tests showed that rigid, poured polyurethane foam is the most applicable backfill solution for deployed locations because of its ability to expand to several times its shipped liquid volume when mixed, reducing the logistical burden of transporting aggregate backfill materials. This paper describes laboratory and field experiments that used foam backfill and prototype equipment to develop a pavement repair technique that supports threshold and objective aircraft pass levels defined for expedient airfield repairs. The research included laboratory testing, full-scale field testing, and simulated and actual aircraft traffic tests with C-17 and F-15 aircraft. Results of these tests validated and certified the foam backfill repair technique for military aircraft use. However, these experiments also identified material and equipment limitations that will require additional research before the repair technique is adopted by military repair teams. Conclusions and recommendations for future equipment and material improvements are provided.

Every year, millions of taxpayers’ dollars are spent maintaining roads. The money is used to repair damage that occurs to pavements, bridges, and other elements of the roadway system. The service life of a pavement can be greatly reduced by unexpected heavy loading, which is one consequence of hydraulic fracturing (fracking) activity in rural areas. This paper describes a tool that can potentially lengthen the service life of pavements, especially thin pavement structures, by predicting unusually heavy loading. Predicting activities that cause increased truck loading can help agencies plan preventive measures to reinforce pavement structures before they fail. The goal of this study was to develop a tool, an early warning system (EWS), that can help to predict locations where damage from heavy truck traffic will occur. Truck travel related to the oil and gas industry is predictable and has recently had significant effects on pavement deterioration. The study focused on well permitting activity in the Austin, Texas, Department of Transportation district. ArcGIS software was used to find route assignments by using trip origins and destinations for fracking activity, truck volume, and vehicle weights. Several road segments that would be at risk for heavy loading and shortened service life were successfully identified. This tool can provide information needed to prioritize proactive pavement maintenance for more effective use of tax dollars. This tool could potentially also be used to determine a roughly proportional cost of damage from fracking activity to be levied on the oil and gas industry, thus alleviating the burden on taxpayers.

Millions of dollars are annually spent for ice or snow removal from the roadways and airport paved surfaces in cold regions. The presence of snow or ice on paved areas can cause traffic accidents and financial loss because of flight cancellations or delays. For mitigating winter pavement maintenance issues, the use of superhydrophobic (super-water-repellent) coating techniques is gaining attention as a smart and cost-effective alternative to traditional snow and ice removal practices. This study focuses on creating, characterizing, and evaluating innovative superhydrophobic coatings on asphalt concrete surfaces for ice- and snow-free flexible pavement applications. The layer-by-layer (LBL) method was used to create an asphalt concrete surface coating with polytetrafluoroethylene (PTFE) as a well-known super-ice- and super-water-repellent material. Superhydrophobicity and skid resistance of the coated asphalt concrete surface were characterized by the water contact angle, the work of adhesion, and the coefficient of friction at the microtexture level. These properties were evaluated for test variables including spray times and dosage rates of PTFE under a statistical design–based experimental test program. The measurement results indicate that uses of the LBL method for spray-depositing the PTFE particles and the microtribometer for measuring coefficient of friction at the microtexture level are promising methods for creating and characterizing superhydrophobic coatings on asphalt concrete. The results of statistical analyses indicate that the spray time and dosage of PTFE significantly affect the ability of a coated flexible pavement to be icephobic or superhydrophobic and skid resistant.

The Georgia Department of Transportation (DOT) has developed and implemented a new pavement preservation method that uses micromilling in conjunction with a thin overlay for cost-effective replacement of a deteriorated, thin, open-graded surface layer (¾ to 1¼ in.) without removing the sound underlying layer. The new method was first implemented in 2007 on a 15.3 mi section on I-75 near Perry, Georgia, and resulted in significant savings. In considering whether to adopt the new method as standard practice in pavement preservation, it is essential to evaluate the method’s actual, long-term performance. This is the first paper to report the actual, long-term performance of the new method. The study used 8 years of pavement condition data collected by the Georgia DOT and sensing data collected by Georgia Institute of Technology. Based on the data, the pavement on I-75 is still in good condition after 8 years (with 6% raveling in 2015). Based on the current condition and the Georgia DOT’s past experience with open-graded surface mixes, the Georgia DOT anticipates an additional 2 to 3 years of service for the I-75 project. This provides a service interval of 10 to 11 years, which is comparable to that of Georgia’s conventional pavement rehabilitative strategy for open-graded surfaced Interstate pavements, which typically ranges from 10 to 12 years. The equivalent uniform annual cost of the new method is $11,200 per lane-mile per year, which is 11% lower than the $12,600 per lane-mile for the conventional rehabilitation method computed on a 12-year service interval. This information can assist transportation agencies in making decisions about whether to apply the new pavement preservation treatment.

A self-consolidating concrete (SCC) mix was developed to accelerate the construction of replacement slabs in concrete pavement rehabilitation projects. This work was part of a larger research project to develop an innovative process involving the use of temporary and reusable precast slabs and an SCC mix for construction of replacement slabs to reduce construction time and increase contractor production in concrete pavement rehabilitation projects. Two requirements were set for the SCC mix, high workability and flow rate without segregation, and a minimum 6-h compressive strength of 2,200 pounds per square inch [psi (15 MPa)] required by the Florida Department of Transportation (DOT). The SCC mix incorporated Grade 57 aggregate as well as a combination of admixtures, including a high range water reducer, workability retainer, water reducer and set retarder, and accelerator. Laboratory trial batches were prepared for the proposed mix and tested for workability and strength. On the basis of test results of the trial batches, the refined SCC mix was developed to achieve the high workability needed for faster concrete discharge and finish and to attain the Florida DOT's 6-h strength requirement of 2,200 psi (15 MPa) for slab replacements.

This paper quantifies the environmental improvements in current versus past pavement materials and construction practices employed by the Illinois State Toll Highway Authority (tollway authority). Improvements in sustainability performance were measured with a life-cycle assessment (LCA) approach. Three scenarios were generated to evaluate tollway authority practices on the basis of eight 2013 Interstate reconstruction and rehabilitation projects. The first scenario, 2013 projects, analyzed the actual pavement material and designs of the 2013 projects. The second scenario, materials baseline, was based on the 2013 projects but modified to include mix designs with less-sustainable materials used by the tollway authority circa 2000. The third scenario, design and materials baseline, considered both mix designs and pavement design practices used circa 2000. To improve the spatial and temporal relevance of the analyses, two regional databases of life-cycle inventories representing processes from 2013 and 2000 were developed and applied to the 2013 projects and 2000 baselines. A tool developed by the Illinois Center for Transportation (ICT) of the University of Illinois at Urbana–Champaign, the pavement ICT-LCA 0.95, was used to evaluate the sustainability performance indicator (SPI), global warming potential (GWP), and cumulative energy demand (CED) for each scenario. The resultant savings in SPI, GWP, and CED from the first scenario ranged between 17% and 28%, 12% and 16%, and 13% and 26%, respectively, compared with the second scenario, and 12% and 33%, 8% and 26%, and 11% and 32%, respectively, compared with the third scenario.

General aviation (GA) airports play an important role in the national transportation system by accommodating emergencies and providing for agricultural, recreational, and other operations. GA airports account for almost 90% of the airports in the Texas Airport System Plan. To protect their initial investment in asphalt and concrete pavements, GA airports are expected to perform routine pavement maintenance. For this case study of pavement maintenance practices at GA airports in Texas, GA airport managers were contacted and interviewed about treatments used at their facilities and about the process of having the work done. Respondents were asked to rank the effectiveness of specific maintenance treatments for asphalt and concrete pavements on a Likert-type scale, as well as marking type, retexturing methods, and rubber and contaminant removal methods. Information about the level at which pavement maintenance decisions were made, the process, and the additional data desired (specifically about pavements) was obtained through open-ended questions. The results show that crack sealing and slurry sealing are the two most commonly used maintenance treatments—in a reactive manner. The results also indicate that most GA airport managers rely on the Aviation Division of the Texas Department of Transportation or an engineering firm to manage the airfield pavement and do not take an active approach to implementing routine preventive maintenance. This reliance was the result of two factors: (a) level of knowledge, of both the airport managers and those approving funding, and (b) availability of funding. Opportunities for cooperation and education to address deficiencies exist within the current system.

Throw-and-roll and semipermanent patches are frequently used pothole patching techniques for asphalt pavement. To evaluate the cost-effectiveness of the two patching techniques with different combinations of materials and procedures, a 14-month survey was conducted to investigate field performance of patches installed on road sections with varying weather and traffic conditions. The performance of a patch was rated according to its overall distress conditions. With failed patches rated as 0, the service time was considered in the performance index. The multiple linear regression method was used to analyze the influence of patching methods, materials, geometric features, climatic condition, and traffic factors on the performance of patches. The field survey found that the throw-and-roll patches installed in winter deteriorated very fast, mainly because of severe freezing environment and insufficient compaction and curing. The 70% throw-and-roll patches lasted less than 14 months. Patches that survived through the first winter were typically well compacted, fully cured, and tended to last much longer. Labor costs accounted for 50% to 60% of the total cost, while material costs accounted for only 20% for cold mixes and 2% to ∼5% for semi permanent patches. Because of the reduced equipment and labor costs, the throw-and-roll patches had higher cost-effectiveness in the short term. However, the effectiveness of throw-and-roll patches decreased rapidly, and semipermanent patches exhibited higher cost-effectiveness in the long term. To improve the stability of patches, it is of great importance to apply sufficient compaction during installation.

Portland cement concrete pavement repair technologies using precast portland cement concrete panels have been investigated for decades and recently have gained acceptance and increased use in the United States for highway pavements but have had only limited use for airfields. The recent field testing of a new airfield precast panel repair system indicated that precast panels were suitable for expedient airfield pavement repairs; the panels could withstand between 5,000 and 10,000 passes of C-17 aircraft traffic. Failure of the panels was due to spalling of the transverse doweled joints. The purpose of this study was to determine the load transfer effectiveness, or load transfer efficiencies (LTEs), of the panel repairs. A heavy weight deflectometer was used to collect deflection data before, during, and after trafficking to calculate precast panel LTE on the basis of deflections (LTEδ) or transferred stresses (LT). The LTE values were then evaluated to determine whether current measures of effectiveness w...

With the emphasis on sustainability in recent years, hot in-place pavement recycling has been widely used in pavement maintenance in China. However, the application of this technology on modified asphalt pavement does not proceed smoothly because the aged modified asphalt in reclaimed asphalt pavement (RAP) mix is difficult to rejuvenate. So far, few effective rejuvenating agents have been developed for modified asphalt. Therefore, new agents or new methods are called for in modified asphalt pavement recycling. The purpose of the rejuvenating agent is to promote the properties of RAP mix through the rejuvenation of the aged binder. Styrene–butadiene rubber (SBR) latex, a polymer emulsion used to blend modified asphalt with conventional asphalt, now is considered to be a new additive agent to take the place of a rejuvenator but achieve the same goal. Tests were conducted in the laboratory to measure the effect of SBR latex on RAP mix. SBR latex was found to enhance the low-temperature properties of RAP binder efficiently without causing any observable negative influence on RAP mix compaction if a proper dosage was applied. Meanwhile, SBR latex was able to improve the viscoelastic characteristics and other performance of RAP mix, including the resistance to low-temperature cracking, rutting, and moisture damage. Finally, the field application in hot in-place pavement recycling proved the feasibility and effectiveness of using SBR latex.

The Michigan Department of Transportation's (DOT) pavement preservation program dates back to 1992. In Michigan, pavement preservation is implemented primarily through the Michigan DOT's capital preventive maintenance (CPM) program, in which preventive maintenance treatments are used to protect existing pavement surfaces, to slow deterioration, and to correct surface deficiencies. An overall objective of the CPM program is to postpone major rehabilitation and reconstruction activities by extending the service life of pavements. Results of a study performed to calculate the benefits and costs of various preventive maintenance treatments used in the Michigan DOT's CPM program are presented. With benefit defined as the percentage increase in performance over a do-nothing or untreated pavement performance curve where data were available, benefits were calculated for preventive maintenance treatments. Benefit–cost ratios were calculated by unit cost, and permitted the comparison of the cost-effectiveness of similar treatments. The overall performance of the Michigan DOT's CPM program was also examined by comparing the life-cycle costs of a rehabilitation strategy to a preservation strategy with the use of a simplified approach. The outcome showed that the preservation strategy resulted in agency cost savings of approximately 25% per lane mile over a rehabilitation-only strategy. Findings from this study can be used to help the Michigan DOT improve its CPM project selection, treatment selection, and performance monitoring and modeling practices.

With the increase in material and labor costs and the decrease in purchasing power, the Texas Department of Transportation (DOT) is striving to maintain its roadways at the current level of conditions within a severely constrained budget. In particular, maintaining adequate pavement skid resistance has become a challenge for decision makers at various levels. The goal of this study was to develop a methodological procedure that could be used to establish the appropriate threshold values for skid resistance so that safety would not be compromised on Texas highways when there is a budget shortfall. The two primary issues were to be addressed: ( a) identification of the quantitative relationship between pavement skid resistance and crash rates and ( b) determination of threshold values for skid resistance and corresponding recommendations for maintenance decisions. A detailed methodological framework was proposed. Highway segments were categorized into homogenous groups of safety-related characteristics, except skid resistance. The quantitative relationship between crash risks and skid resistance was then established with the concept of the crash rate ratio. Three threshold values were determined to establish four decision categories of skid resistance values, with crash and skid resistance data collected from 2008 to 2011 on the highway system maintained by the Texas DOT. Corresponding recommendations on maintenance decisions were provided. The results show that the proposed methodological procedure can effectively capture the safety impacts of skid resistance at the network level and provide a useful tool for the Texas DOT to take safety into its maintenance decision-making processes.

In recent decades, state, local, and federal use of asphalt concrete overlays to rehabilitate portland cement concrete pavements has increased significantly. This growth has increased the attention given to mechanistic– empirical modeling of reflective cracking. This paper describes recent research that assessed and modified the state of the art in mechanistic– empirical modeling of reflective cracking. The research reviewed the original Mechanistic–Empirical Pavement Design Guide model and the CalME reflective cracking model. The paper also details research in which the CalME model was modified to facilitate its integration into the design guide for pavement projects of composite asphalt concrete over portland cement concrete.

This paper presents a new optimization model for addressing the problem of planning pavement maintenance, rehabilitation, and reconstruction (MRR) for a large-scale road network. In the past, this problem has usually been formulated as a linear programming or integer programming model. The solutions obtained from those models determine the timing, location, and type of treatment needed to perform the MRR operation for a given planning horizon. A shortcoming of such models is that the sections selected for MRR are usually distributed spatially across the network, and this distribution makes it difficult to plan and implement MRR activities in a coordinated manner. To take advantage of economies of scale, adjacent road sections with similar MRR needs should be maintained within a single project. However, the idea of automatically combining adjacent sections into one large project has not been given serious attention in existing optimization models for pavement MRR planning. This paper proposes a new approach to pavement MRR planning that utilizes the spatial structure of the road network. The road network is first partitioned into groups of adjacent sections, or MRR projects, with similar MRR needs. Then a knapsack problem is solved to optimally allocate resources to selected MRR projects with the objective of maximizing system performance.

This paper highlights the challenges in developing practical concrete pavement patching specifications for the Virginia Department of Transportation (DOT). Several hypothetical scenarios were analyzed with HIPERPAV to provide a general idea about the sensitivity of the parameters that affect the performance of concrete patches. The study concluded that the use of a maturity meter in the Virginia DOT special provisions will allow a rapid decision to be made regarding early opening to traffic after concrete repairs and will eliminate the need for testing during construction. Specifying a compressive strength of 1,600 psi (11,030 kPa) for opening to traffic will not adversely affect the patch. Contractors can use HIPERPAV to compare various strategies including placement time and traffic opening time for a particular concrete mix. In general, at higher mix temperatures, the peak stress-to-strength ratio is consistently higher over longer times. It is important to control or minimize the base and subbase temperature before concrete is poured. Higher early cracking potential is associated with patch mixes with a lower water–cement ratio. The early cracking potential is higher in longer patches compared with shorter patches in spite of the similar strength gain requirements for opening to traffic. The risk of failure is low for a shorter patch when the traffic opening time is reduced.

The pavement structural number (SN) is used in various applications worldwide. One application is the structural condition index. The structural condition index was developed for the Texas Department of Transportation (DOT) to support maintenance and rehabilitation decisions at the network level and is calculated as the ratio of two SN values (effective SN/required SN). A direct method of determining the SN from falling weight deflectometer (FWD) testing has been used to evaluate the effective SN. This study sought to increase the accuracy of the structural condition index by improving the method of determining the effective SN from FWD deflection data. A new equation was developed by modifying the equation that was previously used, and new coefficients for four different flexible pavement types were used. The new equation was improved by the addition of new variables for considering the depth to a rigid layer and by the use of a large database consisting of hypothetical pavement structures and responses. This effort not only benefits the Texas DOT by allowing increased accuracy in implementing the structural condition index but also helps other agencies improve their evaluation of the SN by FWD deflection at the network level. In this study, only surface-treated pavement and asphalt concrete pavement were evaluated; portland cement concrete pavement was not addressed.

The Texas Department of Transportation has by far the most continuously reinforced concrete pavement (CRCP) lane miles in the nation, and sections as old as 50 years are still in service. Having served much longer than intended, some sections are showing distress. Full-depth repair (FDR) is one of the methods used to repair CRCP distresses in Texas. Over the years, various FDR methods have been used, and the effectiveness of each method has varied. In the most widely used FDR method, a full-depth cut is made at a minimum of 1.5 ft (0.46 m) inside the transverse repair boundaries, a partial-depth cut is made at repair boundaries, and the concrete between the cuts is removed to expose longitudinal steel. The method has inherent disadvantages, the longer repair time being the primary one. The full-depth cut FDR method, in which a full-depth cut is made at the repair boundaries and longitudinal tie bars are epoxy grouted into the existing concrete, has advantages over other methods, including a faster operation that minimizes roadway closure time. Because CRCP is normally used in areas with high traffic volume, the maximum time the Texas Department of Transportation allows for the FDR operation is usually 9 h, which makes the full-depth cut method the only acceptable repair method. Factors affecting the effectiveness of the full-depth cut method were investigated with laboratory testing and field evaluations. The method of epoxy injection, keeping the epoxy in the holes after insertion of the tie bars, restoring base support, and the length of the embedded tie bar were the most important variables affecting the performance of FDR. Recommendations were made to revise specifications for FDR and epoxy materials on the basis of these research findings. Implementation of the recommendations should result in improved FDR performance of CRCP.

The Alaska Department of Transportation and Public Facilities (DOT&PF) wished to enhance its existing pavement preservation management program by using effective pavement preservation treatments for cold regions. This initiative would extend pavement life and defer the need for more costly rehabilitation. By collaborating with the California Pavement Preservation Center and the Alaska University Transportation Center, the Alaska DOT&PF recently completed a pavement preservation research project to improve its pavement preservation program for flexible pavements. Research tasks included conducting an international survey of pavement preservation in cold regions, reviewing literature on cold region pavement preservation treatments, monitoring existing preservation treatments that Alaska used, developing a pavement preservation database, and creating an online computer program for treatment selection. The database for pavement preservation treatment tracking is a web-based online program that includes standard types of pavement preservation strategies used in Alaska; pavement construction, traffic, weather, and other performance-related information; an integrated Google Map function to show the location of pavement preservation projects; and multiple pavement condition survey results with supporting documents. The strategy selection program is integrated within the pavement preservation database. The program sees results of the survey and other information on Alaska treatments to conduct treatment strategy selection and life-cycle cost analysis. Workshops have been given on preservation treatments used in cold regions and use of the database and strategy selection process. Tools developed for the Alaska DOT&PF should be helpful for long-term implementation of an effective pavement preservation program. Other agencies could learn from Alaska's experience.

Pervious concrete pavement (PCP) is used because of its unique properties that allow water to infiltrate into the surface. The objectives of the study reported in this paper were to observe the performance of PCP in the field, determine the effectiveness of cleaning methods to restore infiltration rates, and compare field observations with laboratory results when possible. Two PCP sites in Vermont were monitored over a year through the measurement of infiltration rates at several locations. Facility-wide cleaning operations, such as street sweeping and vacuum-truck cleaning, were tested for their capability to restore infiltration rates. Spot-cleaning methods, such as hand vacuuming, pressure washing, and a combination of the two, were also tested. Infiltration rates decreased gradually during the monitoring period, with average reductions of 59% at the first facility and 26% at the second. Street sweeping and vacuum-truck cleaning restored infiltration rates by 21% and 30%, respectively, but could not restore severely clogged areas. Spot-cleaning methods increased infiltration rates by 85% after pressure washing, 10% after vacuuming, and 100% after pressure washing followed by vacuuming. Vacuum-truck cleaning was recommended. Either method, however, should be used for maintenance operations and should be started after construction. Spot-cleaning methods, with the exception of vacuuming, restored infiltration rates of severely clogged areas and were recommended for localized cleaning. Long-term monitoring compared reasonably well with that of earlier studies, whereas the results associated with cleaning were substantially lower than those found in the literature.

This study focuses on large-scale pavement maintenance and rehabilitation planning. Pavement agencies usually deal with large and diverse networks of thousands of pavement sections. The complexity of pavement maintenance and rehabilitation planning increases exponentially with the size of the network. Exact optimization methods designed for small-scale problems thus suffer from dimensionality, which significantly compromises the ability to solve such problems in a reasonable time period. Consequently, such problems should be approached from the technique of approximation. A method with the Lagrangian relaxation technique and a branch-and-cut algorithm is proposed for use as a decomposition scheme for pavement maintenance and rehabilitation planning problems when the size of the problem poses a major hurdle for its solution. The proposed approach first decomposes the network (original problem) into individual sections (subproblems) and then solves the subproblems separately. As shown in the case study, the proposed approach is able to solve problems with a practical size efficiently. More specifically, the results show that the proposed method can solve problems with a network of 1,000 sections within a reasonable time period and can yield a solution close to the optimal one.

Most state departments of transportation (DOTs) adopted the Superpave® mix design method in the late 1990s. The Superpave mix design method replaced the Marshall method and became mainstream. Superpave came with aggregate, binder, and mix requirements to control rutting and cracking. With a life expectancy of about 15 years, many Superpave roads are now becoming candidates for resurfacing or recycling. Can Superpave mixes undergo hot in-place recycling with success? In fact, Superpave mixes contain expensive and high-quality aggregates, which meet the consensus properties, and high-quality binder, which meets the performance grade (PG) requirements. If these mixes can be recycled in place and meet the original Superpave properties, then substantial savings can be realized. The potential savings are in the 30% to 50% range of the cost to mill and resurface. In addition, emissions could be reduced by 70%, while 100% of the existing material could be reused. This paper reports on an experiment conducted in Gainesville, Florida, in 2010 at the Florida DOT State Materials Office, in which a Superpave mix underwent the hot in-place recycling process. The properties of the aggregate, binder, and mix were compared to answer certain questions about aggregate degradation, binder rejuvenation, and mix properties. The answers to these questions shed light on the possibility of the 100% recycle of Superpave mixes. The results showed that minimal aggregate degradation took place. The recycled mixes met Superpave gradation requirements for the most part. The rejuvenated binder met or exceeded the PG requirement. The mix could be engineered to meet the air voids requirement of Superpave.

The micromilling technique to mill asphalt surface mix continues to be studied in the state of Georgia as part of a pavement preservation treatment in conjunction with thin asphalt overlays. Earlier research showed the results of micromilling on a deteriorated open-graded surface, which was overlaid with a new open-graded surface on I-75, south of Macon, Georgia. The micromilling produced a much finer surface texture than did conventional milling, with a ridge-to-valley depth (RVD) of less than 3 mm, and the technique could more accurately mill the deteriorated open-graded layer. A new open-graded surface was placed on top of that layer with no need for a new dense- or gap-graded layer. The result was a large cost savings compared with conventional milling and overlay. This paper summarizes research performed on a micromilling and open-graded inlay project on I-95 near Savannah, Georgia, and compares the results with those from the previous research. The new research affirms that significant cost savings can be achieved through the replacement of conventional milling with micromilling. Results obtained from the I-75 project indicated that, on the basis of 3 years of satisfactory performance of the open-graded overlay on the micromilled surface, the use of the 95th percentile RVD parameter as the threshold value for compliance with the 3.2-mm RVD acceptance requirement could be too conservative. Results from the I-95 project indicated that the mean RVD of the micromilled surface could meet the 3.2-mm RVD requirement. However, the appropriateness of this parameter's use should be determined on the basis of the long-term performance of the open-graded mix placed on the micromilled surface.

In the past, highway authorities have selected pavement treatment type on the basis of the driving lane conditions and have applied the same treatment to all lanes. Recently, authorities started applying different treatments to the driving and passing lanes at different times. Because of costs, most highway authorities collect only the driving lane pavement condition data. Therefore, the passing lane pavement conditions need to be modeled with the driving lane data. To address this need, time series pavement condition and distress data along the driving and passing lanes of the Minnesota Road Research Project were obtained. The data were analyzed to develop and verify methodologies to estimate the passing lane conditions and distresses accurately with the use of the measured driving lane data. The methodologies are based on the fact that most pavement distresses are caused by material and environmental factors and by traffic loads. The effects of the first two factors are similar on adjacent driving and passing lanes. The differences in the conditions between adjacent lanes are mainly because of traffic distribution, which is expressed by the lane distribution factor. The developed methodologies use the measured pavement conditions along the driving lane and the lane distribution factors to estimate the time series conditions of the passing lane. For asphalt pavements, the time-dependent conditions of the passing lane can be accurately estimated (with low standard errors) with the measured conditions of the driving lane and the lane distribution factors. Procedural steps for implementing the methodologies are included.

Transportation engineers, planners, and policy makers are currently faced with the need to incorporate sustainability issues such as energy use, greenhouse gas emissions, and overall health impacts into the decision-making process. Life-cycle environmental analysis (LCEA) is one of the evolving tools available to assist in this effort. LCEA differs from traditional environmental analysis in that LCEA takes a more comprehensive look, or global perspective, at the environmental and resource burden of specific management decisions as opposed to traditional environmental analysis, which tends to focus almost exclusively on specific impacts at the activity or in the immediate geographic vicinity of the activity. The results of a study are presented: the computer program Pavement Life-Cycle Assessment Tool for Environmental and Economic Effects (PaLATE) was used to compare the environmental burden of employing cold in-place recycling with the environmental burden of the conventional maintenance options of a 3-in. mill and fill and a 3-in. hot-mix asphalt overlay. The results illustrate the potential of life-cycle environmental models to assist transportation officials in developing 21st century transportation policy as well as the current limitations associated with their use.

Because of the decline in aggregate supplies and the need for durable and rut-resistant hot-mix asphalt (HMA), the use of surplus fine aggregates in 4.75-mm mixes could be beneficial for HMA producers, aggregate suppliers, and highway agencies. The primary focus of this paper is to describe the development of and evaluate 4.75-mm Superpave® mixes for use in thin overlays on non-Interstate highway pavements and maintenance applications. The asphalt pavement analyzer (APA) is used to examine the rut resistance of the 4.75-mm mixes. The acceptable APA rut depth was specified to be 9.5 mm. Because of the nature of the 4.75-mm mixes, the Superpave mix design was adjusted to avoid the production of mixes with excessive asphalt contents. A 6% air void design was crucial for the success of North Dakota's 4.75-mm mixes. The research study entailed four mix design cases involving two binders and two aggregate blends with different proportions of natural and crushed fines. Laboratory specimens were produced at 7.0% air voids, heated to either 64°C or 58°C for 6 h, and made to endure 8,000 APA loading cycles. The results indicate that all mix design cases were rut resistant and that mixes with higher percentages of crushed fines performed the best. For the design cases in which only the asphalt binder grade (PG) is the variable, the specimens were tested at different temperatures, so the results could not be compared, but a trend for an increase in rut depth with higher asphalt concrete contents was observed. Trial mixes with high percentages of natural fines failed the APA rut depth tests.

Innovative pavement rehabilitation techniques, such as in-place recycling, are becoming more prevalent as highway agencies face an ever-increasing list of pavement maintenance needs and declining or stagnant budgets. Full-depth reclamation (FDR) has been shown to be a cost-effective alternative to deep milling and repaving to rehabilitate deteriorated flexible pavements. The results of previous FDR studies that investigated pavement structural capacity through the use of deflection testing suggest that long-term strength gain may be achieved through curing; however, such a strength gain has not been well quantified. This study documented the in situ structural testing, with a falling weight deflectometer, of three FDR projects constructed in 2008. Deflection testing was performed periodically at the project sites in the first 2 years after reclamation. This study showed that an accurate estimation of the final structural capacity of an FDR project may not feasibly be achieved immediately after the project has been completed and that it could vary greatly depending on the stabilizing agent used. If data from early-age testing are used to calculate design parameters for future projects, the parameters may be too conservative and result in the loss of potential cost savings through the use of unnecessary overlay materials. A cost analysis, based on data collected in this study, showed that these potential cost savings could approach $37,000 per lane mile. Further mechanistic-based studies of the time-dependent structural response of FDR materials are recommended.

Classic engineering economic theory was developed to furnish the analyst with a tool to compare alternatives on the basis of life-cycle cost (LCC). However, tools used to apply theory to transportation focus on new construction projects with relatively long service lives. These tools do not accurately model the economic aspects of short-lived alternatives such as those that pavement managers must evaluate when seeking the most cost-effective pavement preservation treatment. The field of pavement preservation seeks to “keep good roads good,” and hence pavement preservation treatments are applied to extend the functional service life of the underlying pavement. No significant research has been done to quantify the actual service lives of the pavement preservation treatments themselves nor has a model been furnished to analyze their LCCs. The paper addresses those two gaps in the pavement economics body of knowledge by proposing a methodology for using field test data to quantify the service lives of pavement preservation treatments for both asphalt and concrete pavements. In addition, the paper concludes that an LCC model based on equivalent uniform annual cost, rather than net present value, specifically addresses the relatively short-term nature of pavement preservation treatments and allows the engineer to better relate treatment LCC output to annual maintenance budgets.

Fatigue cracking in asphalt mixtures—a common, widely studied mode of distress in flexible pavements—necessitates major investments in pavement maintenance and rehabilitation. To date, research has focused on the response of bituminous mixes subjected to cyclic loading until failure. Moreover, low-temperature thermal stresses in bituminous mixes have been investigated in isolation to determine the effect of thermal gradients on materials. However, decreased temperature leads to a combined effect of fatigue distress and thermal stress. To provide insight into this phenomenon, an experimental study based on a new test procedure developed by the Road Research Laboratory of the Technical University of Catalonia, Spain, is presented. This method allows the simultaneous evaluation of the effect of thermal stresses and the fatigue response of asphalt mixtures.

If chip seals are constructed properly, they are a cost-effective means of extending the useable life of hot-mix asphalt pavements. Over the years, chip seals have been criticized because they sometimes do not perform as expected. This paper discusses the steps necessary to build chip seals that perform well, including project selection, specifications, material quality, and construction methods.

In network-level pavement management, maintenance prioritization of pavement segments usually involves determining the relative priorities of pavement segments with several distresses of various types and severity levels. A widely adopted practice is to assign maintenance priority to each pavement segment with a priority index computed with an empirical mathematical equation. Though convenient to use, the computed numerical index does not have a clear physical meaning, and it may not accurately and effectively convey the priority assessment or intention of highway agencies and engineers. The analytic hierarchy process (AHP) has been adopted to overcome this limitation. The AHP was previously applied to establish the relative pavement maintenance priorities of single pavement distress types with different severity levels. The problem of establishing maintenance priorities of pavement segments with multiple distresses is much more complex. Many more decision levels and pairwise comparisons must be made because of many possible combinations of distress types and severities. The AHP formulation of the problem is presented, along with a demonstration of an example problem consisting of 30 multidistress pavement segments. The solution of priority ratings by the AHP is compared with the corresponding solution by the widely adopted PAVER pavement maintenance procedure. The reasonableness of the two solutions is compared with the priority ratings obtained from a direct assessment method that provides the baseline reference for comparison.

Selected equipment and procedures were evaluated to expedite repair of spalls with rapid-setting materials. The objective was to develop one or more methods to excavate and prepare a 2-ft2 × 4-in. deep spall for placement of a rapid-setting repair material in 15 min or less. A secondary objective was to correlate various excavation methods with a relative life expectancy of the repair. For five excavation methods, 2-ft2 × 4-in. deep spalls were excavated in triplicate. The spalls were subsequently repaired with a commonly used rapid-setting spall repair material. The efficacy of the repair methods and equipment were evaluated on the basis of petrographic examination of the substrate excavation, production rate, total production rate, in situ tensile pull-off strength, direct shear bond strength, and performance under simulated F-15E wheel loading. Each of the methods evaluated had a significant improvement in production rate over the 30-lb jackhammer, the standard Department of Defense spall repair excavation method. The most efficient method was a cold planer, which, on average, was approximately 58% more efficient than the jackhammer. Of the methods evaluated, only the cold planer could meet the requirement of excavating a 2-ft2 × 4-in. deep spall in no more than 15 min.