AASHTOWare Pavement ME Research Articles

Surrogate modelling of surface roughness for asphalt pavements using artificial neural networks: a mechanistic-empirical approach

ABSTRACT Pavement surface smoothness (or roughness) is crucial for traffic safety, driving comfort, and fuel efficiency. As a widely applied roughness indicator, an accurate forecasting of the International Roughness Index (IRI) and its deterioration is essential for the design, maintenance, and management of asphalt pavements. Previous studies have used field measurement data or AASHTOWare Pavement ME Design simulations for the development of machine learning (ML) models to streamline the IRI modelling. However, these models frequently lack the accuracy and robustness of the measurement data or high-fidelity computational simulations they are intended to surrogate. To address this issue, we employed a new adaptive sampling technique to generate an informative yet efficient pavement damage database from Pavement ME simulations. Utilising Artificial Neural Networks (ANNs), we engineered two types of surrogate ML models: (a) Model I, an ANN-based IRI predictive model, and (b) Model II, a hybrid model combining ANN-based predictions of rutting, fatigue damage, and thermal cracking with closed-form relationships between these indicators and IRI. Our findings show that Model II outperforms Model I in IRI modelling accuracy both globally and locally. Moreover, Model II matches IRI simulations of Pavement ME while providing enhanced efficiency and adaptability to a broader spectrum of design considerations.

Rheological properties of plastic-modified asphalt binders using diverse plastic wastes for enhanced pavement performance in the UAE

The integration of waste plastics in asphalt mixtures has recently gained more popularity as a potential solution for repurposing waste plastics, while relieving the accumulation of plastics in landfills. This paper investigates the addition of plastic wastes from four waste products namely HDPE, PET, ABS, and LDPE, to asphalt binder at two contents of 2 % and 4 % by the weight of asphalt binder. The control and plastic-modified asphalt binders were tested for physical and rheological properties. Most of the used waste plastics increased the rutting parameter of the asphalt binder. The 4 % ABS plastic-modified asphalt binder managed to achieve the maximum Performance Grade (PG) of 82 while the 4 % PET achieved PG 76. Higher plastic content yielded higher resistance to permanent deformation. Asphalt binders modified with 2 % LDPE and 2 % HDPE yielded the best performance against low temperatures. The Linear Amplitude Sweep (LAS) test results at intermediate temperature showed that the best fatigue performance was attained using 4 % ABS at a strain level of 2.5 %, whereas at 5.0 % strain level, the 2 % PET achieved the maximum fatigue improvement (25 %) over the control. Simulated pavement performance using the AASHTOWare Pavement ME Design software showed noticeable extensions in pavement life for the plastic-modified asphalt binders against permeant deformation and fatigue cracking. The Life Cycle Cost Analysis (LCCA) displayed a reduction in the estimated LCCA cost for the plastic-modified asphalt binders by up to 50 % over the control.

Impact of cement content in cement bound materials on the reflection cracking performance of asphalt pavements

This study investigates the impact of cement contents in cement bound material (CBM) on asphalt pavement reflection cracking, considering two levels: 4.5 % (CBM1) and 5.4 % (CBM2). Mechanical properties of CBMs, including elastic modulus, rupture modulus, and thermal expansion, were evaluated. Simultaneously, properties of asphalt pavement layers (wearing course and base course) underwent assessment through dynamic modulus, flow number, and overlay tests. Resilient modulus tests were conducted for subbase and subgrade layers. Laboratory test outcomes served as inputs for a AASHTOWare Pavement ME Design program. The results indicated that despite CBM2's higher elastic modulus and rupture modulus, CBM1 outperformed in pavement design. Based on the outcomes from pavement design program CBM1 exhibited lower total transverse cracking (400.19 m/km) compared to CBM2 (403.38 m/km) after 6 years of service. The higher cement content in CBM2 was identified as a potential contributor to increased cracking, attributed to shrinkage during cement hydration process. Moreover, the higher cement content showed a higher coefficient of thermal expansion (CTE), where CBM1 displayed a CTE of 70 µm/°C, while CBM2 material had a CTE of 40 µm/°C. These findings emphasize the intricate relationship between cement content in CBM and pavement performance, crucial for effective design considerations.

Using mechanistic-empirical simulations and nonparametric testing to explore variability in the expected performance of reference asphalt pavement designs

This study explored the variability in expected performance of eight reference asphalt pavement designs using AASHTOWare pavement ME software. Nonparametric tests showed that structures with a high-modulus asphalt base on an unbound base significantly delayed maintenance. Varying pavement layer materials significantly affected the simulations, except the asphalt surface and asphalt base (when used on an unbound base). Moreover, recycling rates in AC asphalt bases over 60% significantly improved performance over no recycling; however, air void content and effective binder percentage seemed to be key in these findings. Finally, this study showed that meeting material specifications does not guarantee equal performance.

Mechanical Properties and Performance of Mixtures with the Same Volumetric Classification

This study investigates the variations in performance among mixtures that are designed for use with the same traffic classification and whether a single mixture class index–volumetrics relationship (IVR) can be applied to all mixtures within that classification. Three surface mixtures, which are intended to serve traffic levels of 3–30 million equivalent single axle loads, were sourced from different regions in North Carolina: the coast; Piedmont; and the mountains. Dynamic modulus, cyclic fatigue, and stress sweep rutting tests were conducted using the asphalt mixture performance tester. Pavement performance simulations were performed using AASHTOWare Pavement ME Design for fatigue cracking predictions and FlexPAVE™ for permanent deformation predictions. The findings indicate substantial differences in mechanical properties, performance indices, and pavement performance among the mixtures despite having similar volumetric properties. The study also shows that an IVR calibrated for a mixture cannot be used to predict the performance of other mixtures within the same mixture classification as the tested mixture. This research highlights the need for restructuring the mixture classification system so that it is based on mixture performance rather than on volumetric design, with the ultimate goal being a performance-based or related specification to eliminate the limitations introduced by the use of volumetric properties.

Mechanical Properties and Performance of Mixtures Containing a High Level of Recycled Materials That Are Designed Using Alternative Approaches

Using recycled asphalt material (RAM) in asphalt mixtures is very common among transportation agencies. With the recent development of balanced mix design methods, it is becoming more important to understand how to optimize mixture performance by offsetting the adverse effects of RAM. In this paper, mixtures from three different sources were adjusted according to the availability adjusted mix design (AAMD) and corrected optimum asphalt content (COAC) methods. Three control mixtures containing RAM, three mixtures containing no RAM, five mixtures designed according to the AAMD method (two of which had 50% reclaimed asphalt pavement content), and two mixtures adjusted using the COAC-based approach were evaluated. Both asphalt mixture performance tester experiments and index tests were used in this study to evaluate material-level indicators of cracking and rutting resistance. Additionally, pavement performance simulations were carried out using AASHTOWare Pavement ME and FlexPAVETM to assess how the observed material-level differences led to differences in structural-level pavement performance. Both the AAMD and COAC methods improved cracking measures. However, the results suggest that the additional virgin binder added through the COAC method without any adjustments to the aggregate structure can have negative consequences for the rutting performance measures. In addition, the mixture and pavement performance results suggest that the AAMD method is a rational approach for including recycled binder availability in mix design procedures to promote improvements in the cracking performance of mixtures by controlling the volumetric properties and the aggregate structure of the mix without having a detrimental effect on rutting resistance.

Life cycle assessment and pavement performance of recycled aggregates in road construction

Integrating environmental goals in the construction of infrastructure has attracted great attention over the past two decades. The use of construction and demolished waste materials (C&D) as a base layer for pavement structures gained popularity as a sustainable alternative to virgin aggregates (VA). An experimental testing program was designed to investigate several recycled materials as a potential replacement to VA in flexible pavements base layer. The testing program included routine tests, matric suction, static, and repeated load triaxial tests to measure the general engineering properties and evaluate the material performance under static and cyclic loading. The results of the laboratory testing program were employed to predict the pavement performance utilizing different combinations of C&D waste as a base layer for flexible pavement structures using the AASHTOWare Pavement ME Design at different climate conditions. The sustainability of using C&D material as a partial or full replacement of VA base material in pavement construction was evaluated by using the life cycle assessment (LCA) approach. The results showed that all the C&D materials yielded a much thinner base layer compared to the natural VA achieving the same pavement performance. Moreover, the reduction in the thickness is more significant in cold and wet climatic conditions rather than the hot and dry climatic conditions. LCA results revealed that the VA base layer had the highest environmental impact on all tested categories. VA materials, used as a base layer, show 65% higher global warming potential compared to C&D materials as a base layer in all climatic conditions.

Resilient behavior of bio-cemented sandy soil treated with enzyme-induced carbonate precipitation for pavement applications

Subgrade stability is a key factor that influences the long-term performance of the pavement structure under repeated traffic loading. Enzyme-induced carbonate precipitation (EICP) has been recently explored as a bio-inspired solution to improve the mechanical properties of sandy soils. This study evaluates the potential of EICP to cement silica sand as a treated subgrade in pavement applications. The study investigated the mechanical performance of EICP-treated sand compacted at varying initial degrees of saturation and treatment cycles through repeated loading triaxial (RLT) and unconfined compressive strength (UCS). The results show that specimens having a lower initial EICP degree of saturation facilitated efficient carbonate precipitation bridging between sand grains, resulting in higher resilient modulus and UCS. Furthermore, surface percolation of EICP cementing solution resulted in a further increase in carbonate content and treated soil UCS and resilient modulus (Mr). A maximum UCS and Mr values of about 700 kPa and 165 MPa, respectively, were achieved, which implies the possibility of using EICP-treated sand as a treated subgrade layer or subbase to reduce the base layer thickness or improve the pavement structure performance. The Scanning electron microscopy (SEM) images further explained the influence of the carbonate crystal shape and morphology on the treated soil strength and modulus. Finally, simulations executed using AASHTOWare Pavement ME Design software show the potential of utilizing EICP for improving subgrade for pavement structures, with a significant reduction in base layer thickness while maintaining the same rutting and fatigue performance. Hence, demonstrating the potential of EICP in enhancing subgrade properties for pavement structures.

Dynamic Modulus Prediction Validation for the AASHTOWare Pavement ME Design Implementation in Egypt

Dynamic Modulus, E* is a crucial property of the hot mix asphalt (HMA). For the AASHTOWare Pavement ME design, E* is an essential material input. E* can be measured in the laboratory or predicted using different models based on some fundamental properties of the HMA. The NCHRP 1-37A and NCHRP 1-40D prediction models are the two main models adopted by the AASHTOWare to predict the E* based on the HMA mixture volumetrics, gradation, and binder properties. The main objective of this research was to validate these two prediction models using local HMA mixes for the purpose of the regional application of the AASHTOWare Pavement ME design in Egypt. For this purpose, the E* values of ten locally plant-produced HMA mixes were measured in the laboratory. The two E* prediction models were then used to estimate the E* values for the same materials. Consequently, the performance of both models was studied by comparing the measured values to the estimated values. The results showed that the NCHRP 1-40D prediction model can satisfactorily predict the E* of the Egyptian HMA mixes with minimal bias and high accuracy. The model yielded an adjusted coefficient of determination (R2) of 0.86 based on 480 E* measurements. On the other hand, the NCHRP 1-37A prediction accuracy was not satisfactory, with very poor accuracy (Adjusted R2 = 0.18) and high bias. Afterwards, the effect of the predicted E* from the NCHRP 1-40D model on the AASHTOWare Pavement ME predicted pavement performance in terms of rutting, cracking, and roughness was further studied. Accordingly, twenty-four simulation runs for typical Egyptian design cases were conducted using, first, the laboratory measured E* values and, then, the NCHRP 1-40D predicted E* values. The results showed that the NCHRP 1-40D predictions had no significant effect on the pavement performance predicted by the AASHTOWare Pavement ME with R2 of the different pavement distresses ranged from 0.980, for the AC rutting, to 0.9996 for the International Roughness Index (IRI). Hence, the NCHRP 1-40D model can be used satisfactorily to predict E* for the Egyptian HMA mixes without compromising the structural pavement design.

Long-Term Performance and Forensic Evaluation of an Asphalt Pavement with Cold Central Plant Recycled Asphalt

In 2012 Virginia Department of Transportation constructed two test sections at the National Center for Asphalt Technology Test Track containing asphalt processed via cold central plant recycling (CCPR) with identical asphalt overlays. One section contained a stabilized base beneath the CCPR layer (Section S12), similar to a full-depth reclamation layer; the other included an unstabilized aggregate base beneath the CCPR layer (Section N4). Both sections were subjected to trafficking by loaded trucks for a total of 30 million equivalent single axle loads. Minor cracking was observed at the surface of the section with the unstabilized base; the section with the stabilized foundation exhibited no surface cracking. Furthermore, strain, pressure, and deflection measurements showed better performance for the section with the stabilized foundation than the section with the unstabilized base. Because of the relatively unchanged performance of Section S12, it was taken out of service to conduct a forensic investigation. This paper presents the analysis of the instrumentation results, coring, trenching, and mechanistic testing and modeling, to better understand and compare the performance between sections. The stabilized base was found to greatly reduce bending action in the section, exhibited no substantial rutting, but also contained what appeared to be some shrinkage cracks. However, these cracks did not propagate to the surface, indicating that the CCPR layer may be an effective crack mitigator. Further, it was found that mechanistic modeling using AASHTOWare Pavement ME design software overestimated the rutting but predicted similar international roughness index and cracking to that observed in the field.

Using mechanistic–empirical based analysis to evaluate rutting performance thresholds for balanced mix design tests

The balanced mix design (BMD) framework uses laboratory test methods to establish specifications that would ultimately be used for the design and acceptance of asphalt mixtures. Assembling such specifications is vital to optimizing the performance of asphalt mixtures for the distress of concern without violating any other criteria, consequently establishing the much desired “balance.” This research presents a stepwise method towards the establishment of performance test threshold criteria for rutting evaluation only as part of a greater effort that the Virginia Department of Transportation (VDOT) is pursuing for the implementation of the BMD framework. Data and discussion of five performance tests addressing rutting performance, along with six representative Virginia mixtures, are presented. AASHTOWare Pavement ME analyses at the material level and project level were utilized to fine-tune observations obtained using the surrogate test methods for rutting evaluation. Potential routes and accompanying challenges towards establishing/refining performance criteria that would prove helpful to the ultimate adoption of BMD specifications were outlined. An example of proposed performance criteria based on the presented data is provided. The proposed performance thresholds for rutting evaluation are intended as indicative; for full development and implementation, further refinement of the values is warranted.

Use of the Iron Chloride Type of Lewis Acid Catalyst in High Reclaimed Asphalt Pavement Content Asphalt Mixtures

The use of reclaimed asphalt pavement (RAP) as a partial replacement for virgin aggregates and asphalt binders has received considerable attention recently. This approach is one of many promising methods for improving sustainability. However, many state Departments of Transportation are cautious in adopting high RAP content into their designs because of cracking and durability issues resulting from the aged RAP binder. A Lewis acid catalyst has been used to modify the asphalt binder’s chemical composition and disrupt the associated molecules formed in the aged RAP binder. The objective of this study is to assess the effectiveness of the use of a Lewis acid catalyst in improving the cracking resistance of an asphalt mixture containing high RAP contents. A suite of laboratory mechanical tests was performed, namely, the dynamic modulus test for linear viscoelastic properties; the semi-circular bend, Illinois flexible index, ideal cracking tolerance, and simplified viscoelastic continuum damage tests for fracture and fatigue resistance; the loaded wheel tracking test for rutting resistance and moisture susceptibility; indirect tensile creep compliance and strength tests for low-temperature cracking resistance; and the Cantabro abrasion test for durability. Further, AASHTOWare Pavement ME software was used to predict the long-term performance of asphalt pavements containing mixtures with high RAP contents and a Lewis acid catalyst. Results showed that the use of the Lewis acid catalyst can disrupt associated molecules formed in the aged RAP binder. Thus, asphalt mixtures containing high RAP contents (recycled binder ratio > 0.20) and a Lewis acid catalyst exhibited similar performances to conventional mixtures. Further, Pavement ME predicted fatigue cracking was lower for a structure containing a FeCl3-modified mixture as compared to a similar one with no FeCl3, illustrating the effectiveness of FeCl3.

Avoiding Disputes in PPP Road Contracts: Quantifying Impacts of Increased Allowable Truck Loads

Dealing with changes is one major concern in long-term public-private partnerships (PPP) concessions, especially during the implementation phase, as some changes might lead to disputes between PPP partners and disrupt the successful execution of the project. In the transport sector, a change in the law regulating truck loading standards inevitably influences the financial stability of road projects procured through PPP. That is, the government’s decision of increasing the permissible truck load can lead to an accelerated deterioration of the pavement, and accordingly imposes additional expenditures that are borne by the concessionaire for maintaining the road condition at a satisfactory level, as required by the PPP contract terms. Given the fact that PPP concessions allow for additional compensations to the concessionaires in the case of modifications in the legislative and regulatory conditions, this study proposes two remuneration strategies for consideration by the concerned government to mitigate the adverse implications of increasing truck load limit on the concessionaire’s financial status and consequently to avoid the occurrence of disputes with the concessionaire. The work presented herein is twofold, as it quantifies the impact of the change in truck load regulations on two main contract terms: the toll regime and the concession period. Under the first approach, the government would provide direct compensation to the concessionaire through a shadow toll paid per overloaded truck. The value of the shadow toll was found to be largely influenced by the truck class, truck load, pavement structure, climatic conditions and traffic volumes. Moreover, it was found that the highest values of shadow tolls would apply to projects with relatively thin pavements and high traffic volumes. Under the second approach, an extension of the concession period was considered, which allows the concessionaire to recover the increased pavement maintenance costs. It was found that the length of the extended term depends, to a great extent, on the project’s characteristics in terms of the pavement structure, climatic conditions, traffic volumes, and more importantly on the toll revenues generated during the extended period. The two proposed alternative compensation techniques were devised and demonstrated through a methodology that involved flexible pavements performance prediction under varying loading conditions, using AASHTOWare Pavement ME. The proposed methodologies represent a framework that helps the two main parties involved in a PPP road project (i.e., the concessionaire and the highway agency) to accurately assess the effect of any increase in truck loading on the pavement performance and to decide on a fair compensation to be offered by the highway agency to the concessionaire, thereby contributing to the avoidance of dispute occurrence.

Evaluating the impact of overweight trucks on rigid pavement performance using AASHTOWare pavement ME design

ABSTRACT The purpose of this study is to evaluate the impact of overweight vehicles on pavement performance over its design life, with Jointed Plain Concrete Pavements (JPCPs) particularly considered for analysis. The Long-Term Pavement Performance database was used to provide information on pavement construction, age, overall structure, specific traffic inputs, and recorded historical pavement performance. AASHTOWare Pavement ME Design (PMED) was used to analyze data extracted from LTPP based on legislation by the Federal Highway Administration (FHWA) regulating gross vehicle weight (GVW) and single and tandem axle weights of overweight trucks (OWTs) to estimate pavement performance and service life. The overall findings indicated that although increasing overweight by 20% on single or tandem axles could considerably reduce pavement service life by up to 20% in the various scenarios examined in this study, OWT exceeding the GVW limit legally-allowed by FHWA could damage pavement more than OWT exceeding axle weight limits.

Sensitivity Evaluation of Short Jointed Bonded Concrete Overlay of Asphalt Pavement in AASHTOWare Pavement ME Design

Sensitivity Evaluation of Short Jointed Bonded Concrete Overlay of Asphalt Pavement in AASHTOWare Pavement ME Design

A comparative study on the performance of field-sampled asphalt mixtures for heavy-duty pavements using laboratory testing and mechanistic-empirical simulations

The demand for durability and resilience in asphalt pavements has led to the progressive implementation of performance-enhancing technologies like bitumen modification using polymers or fibers. This is particularly important in a port environment, where roads are subjected to heavy traffic. The main objective of this study is to contribute to the current state of knowledge on the performance of asphalt mixtures, including polymers and fibers, by conducting a comprehensive laboratory investigation of eight field mixtures, followed by an evaluation of their expected performance in five test sections using the AASHTOWare Pavement ME Design software. The eight mixtures included two lean asphalt mixes to be used as a replacement for granular layers, three base mixtures, and three surface mixtures. Laboratory testing showed that the addition of a blend of 91% polypropylene and 9% glass fibers increased stiffness and resistance to moisture damage. Also, this fiber blend improved cracking resistance when used in a relatively flexible mixture. It was found that top-down cracking predictions followed the trend observed in semicircular bending tests. Conversely, the predicted rutting performance did not align with the rut depth trend in the laboratory. Furthermore, the use of SMA instead of a dense-graded surface layer appeared to increase fatigue cracking in pavement sections with granular bases unless a high-modulus base asphalt layer was used. This study was a first attempt to use advanced pavement performance predictions in Belgium. The data gathered during the future monitoring of the test sections built as part of this study will provide valuable primary data for the local calibration of pavement distress models.

A Machine Learning Tool for Pavement Design and Analysis

The AASHTOWare Pavement ME Design program is a pavement analysis tool, which is typically used for design purposes through an iterative trial-and-error process. To help the designer with a reasonable starting point in this iterative process, this paper introduces a machine learning method to embrace the recently updated models in AASHTOWare Pavement ME Design software for pavement design. A total number of 79,600 pavement design scenarios (55,800 for flexible pavements and 23,800 for rigid pavements) were performed using the AASHTOWare Pavement ME Design software to consider various design inputs, such as: design life, traffic volume, climate zone, thickness, and modulus of pavement layers. The inputs and outputs of these design scenarios were used to develop the multioutput Random Forests model to simultaneously predict multiple pavement distresses and thicknesses of pavement layers. The results indicate that the multi-output Random Forests model can accurately predict pavement distresses and thicknesses for asphalt and concrete pavements. This tool will simplify pavement design procedure based on the models in the AASHTOWare Pavement ME Design software.

The influence of truck speed on pavement defects

ABSTRACT The response of asphalt material depends on the rate of loading and varies from elastic to plastic. Therefore, the behaviour of flexible pavement would also be different along the entire length of a road because of truck speed changes due to the existence of police checkpoints, bus stations, speed bumps, intersections, horizontal and vertical curves, and climbing lanes. The objective of this study is to investigate the effect of truck speed on the performance of flexible pavement. Thus, analyses were conducted for various truck speeds (1–75 km/hr) on three different pavement structures and three traffic levels using AASHTOWare Pavement ME Design 2.5.5 for the local conditions of Izmir, Turkey. The analysis results of the study manifested that a reduction in traffic speed (75–1 km/hr) on a road resulted in higher pavement distress. According to the results, reducing truck speed from 25 to 1 km/hr resulted in a rapid increase in AC rutting, alligator cracking and top-down cracking by 13.3 mm, 10.6% and 1473.8 m/km, respectively. It is expected that the outcomes of this study would promote the local calibration of the mechanistic-empirical pavement design guide (MEPDG) and pavement design in Turkey and the region.

Multi-gene genetic programming extension of AASHTO M-E for design of low-volume concrete pavements

The American Association of State Highway and Transportation Officials Mechanistic-Empirical Pavement Design Guide (AASHTO M-E) offers an opportunity to design more economical and sustainable high-volume rigid pavements compared to conventional design guidelines. It is achieved through optimizing pavement structural and thickness design under specified climate and traffic conditions using advanced M-E principles, thereby minimizing economic costs and environmental impact. However, the implementation of AASHTO M-E design for low-volume concrete pavements using AASHTOWare Pavement ME Design (Pavement ME) software is often overly conservative. This is because Pavement ME specifies the minimum design thickness of concrete slab as 152.4 ​mm (6 in.). This paper introduces a novel extension of the AASHTO M-E framework for the design of low-volume joint plain concrete pavements (JPCPs) without modification of Pavement ME. It utilizes multi-gene genetic programming (MGGP)-based computational models to obtain rapid solutions for JPCP damage accumulation and long-term performance analyses. The developed MGGP models simulate the fatigue damage and differential energy accumulations. This permits the prediction of transverse cracking and joint faulting for a wide range of design input parameters and axle spectrum. The developed MGGP-based models match Pavement ME-predicted cracking and faulting for rigid pavements with conventional concrete slab thicknesses and enable rational extrapolation of performance prediction for thinner JPCPs. This paper demonstrates how the developed computational model enables sustainable low-volume pavement design using optimized ME solutions for Pittsburgh, PA, conditions.

Comparative Study of Pavement Rehabilitation Using Hot in-Place Recycling and Hot-Mix Asphalt: Performance Evaluation, Pavement Life Prediction, and Life Cycle Cost Analysis

The use of hot in-place recycling (HIR) for pavement surface rehabilitation has gained increasing attention in recent years with the aim of achieving sustainable pavement. For the purpose of cost saving and the consumption of 100% reclaimed asphalt pavement (RAP), an in-place HIR train has been developed to combine various units including preheating, milling, rejuvenating, and compacting. Compared with the conventional hot-mix asphalt (HMA) surface treatment, the HIR technique might result in different pavement performances as a result of the low mixing temperature and insufficient quality control. This study aimed to conduct a comparative analysis of pavement surface rehabilitation using HIR and HMA, including the performance evaluation, pavement life prediction, and life cycle cost analysis (LCCA). HIR and HMA mixes were collected from construction areas and the nearby asphalt plant, respectively. The loose mixes were reheated and compacted for performance testing, including dynamic modulus tests, Superpave IDT tests, and moisture susceptibility tests. The AASHTOWare Pavement ME Design software was adopted to predict the pavement life with two rehabilitation techniques, followed by the LCCA with regard to the prediction results. Test results showed that pavement surface rehabilitation with HIR achieves acceptable performance and economic benefits. However, the HIR mixes are brittle and more susceptible to cracking and, therefore, have shorter pavement service lives than HMA.