AASHTOWare Pavement ME Design Software Research Articles

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.

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.

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.

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.

Development of Cost-Effective High-Modulus Asphalt Concrete Mixtures Using Crumb Rubber and Local Construction Materials in Louisiana

One of the emerging solutions to enhance the durability of asphalt pavements is the use of a French asphalt mix known as “High-Modulus Asphalt Concrete (HMAC).” This mix uses a hard asphalt binder, high binder content (about 6%), and low air voids content as compared with Superpave mixtures. The key objective of this study was to develop a cost-effective HMAC mixture using crumb rubber and local materials in Louisiana. To achieve this objective, four HMAC mixtures were prepared using two asphalt binders (PG 82-22 and PG 76-22 plus 10% crumb rubber) and two Reclaimed Asphalt Pavement (RAP) contents (20% and 40%); additionally, a conventional Superpave mixture in Louisiana was prepared as a control mixture. The laboratory performance of these five mixtures was evaluated in relation to workability, dynamic modulus, rutting resistance, and cracking resistance. The AASHTOWare Pavement ME Design software was also used to estimate the long-term field performance of these mixtures. Results indicated that the HMAC mixture prepared with 10% crumb rubber and 20% RAP successfully met the French mix design specifications for HMAC and LaDOTD specifications. This HMAC mix outperformed the control Superpave mix in relation to dynamic modulus, rutting resistance, and cracking resistance. Additionally, this HMAC mixture can reduce the required asphalt thickness by 1.5 or 2 in. based on traffic level. The cost-effectiveness analysis indicated that this HMAC mixture was more cost-effective than conventional Superpave mixtures in Louisiana. In addition, this mixture is environmentally friendly as it can reduce the disposal of scrap tires in landfills.

Local calibration and Implementation of AASHTOWARE Pavement ME performance models for Oklahoma pavement systems

ABSTRACT AASHTOWare Pavement ME Design software was developed as an advanced pavement design tool based on the mechanistic-empirical pavement design guide. Existing performance prediction models utilised in this design guide are nationally calibrated, and it is essential to calibrate these models based on the specific local materials and environmental conditions, and pavement performance information. In this study, Pavement ME Design prediction models, including IRI, rutting, top-down and bottom-up fatigue cracking, and transverse cracking models were calibrated for the state of Oklahoma. The predictions from distress and international roughness index models were evaluated and compared with the measured distress values, and the accuracy and bias terms of each model were determined. Nationally calibrated models showed large errors and significant bias values, which asserts the need for local calibration. Locally calibrated coefficients of distresses and international roughness index models for the Oklahoma pavement system were determined. Predictions from calibrated models show that the use of calibrated coefficients improves Pavement ME predictions and the design of flexible pavements in the state. The impact of the local calibration of Pavement ME on flexible pavement designs was analysed. Locally calibrated models lead to lower IRI prediction and higher fatigue cracking and rutting in the designs.

Predicted impact of design parameters in asphalt concrete layers on pavement performance

The scope of this study was to assess the predicted impact of design factors (voids percentage (Va), effective binder content (Vbe) and aggregate gradation) in each asphalt concrete (AC) layer on pavement performance for conditions in Izmir, Turkey. Research was conducted on three flexible pavement structures for three traffic levels and three subgrade types using AashtoWare Pavement ME Design software. The results indicated that increasing Vbe (from 8% to 15%) and Va (from 3% to 5%) in the wearing course resulted in, respectively, almost 1.0 mm and 0.2 mm increases in AC rutting depth, 17 m/km and 145 m/km reductions in thermal cracking length and a 55.8 m/km decrease and 85 m/km increase in top-down cracking length. For the binder course, an increase in Vbe (from 7% to 14%) and Va (from 4% to 6%) led to, respectively, nearly 1.0 mm and 0.3 mm increases in AC rutting depth and a 35 m/km increase in top-down cracking length. For the AC base course, an increase in Vbe (from 6% to 12%) and Va (from 5% to 6%) resulted in a 26.3% reduction and 14.2% increase in alligator cracking area, respectively. An increase in the fine aggregate percentage and a decrease in the coarse aggregate gradation in the hot-mix asphalt mixture led to improved performance.

Fatigue behaviour of conventional and rubber-modified gap-graded asphalt mixtures using bending and axial fatigue tests

ABSTRACT The study presented in this paper assesses and compares the laboratory fatigue performance of two gap-graded asphalt concrete (AC) mixture: one using crumb rubber (CR) (rubber-modified) and without using CR (conventional). The rubber-modified and conventional gap-graded mixtures were sampled from the E18 highway located in the Stockholm area of Sweden. The testing program consisted of dynamic modulus, |E*|, bending beam, and axial fatigue tests. The |E*| master curves of the respective AC mixtures and their generalised fatigue model coefficients (k 1, k 2, k 3) from the axial fatigue tests were used to predict and compare the long-term pavement performance of each mixture using the AASHTOWare Pavement ME Design software. This analysis was performed systematically using parametric variations to assess the sensitivity of the predicted performance to individual material factors. Fatigue test results from both bending beam and axial fatigue tests showed clear evidence of improved fatigue behaviour for the rubber-modified gap-graded mixture compared to the conventional gap-graded mixture. The Pavement ME design analysis showed that the rubber-modified gap-graded mixture outperformed the conventional mixture. The parametric sensitivity analysis showed that this improved behaviour was the result of an increase in k 1 and decrease in k 2 of the fatigue life relationships at individual test temperatures of the rubber-modified gap-graded mixture. It was also found that the |E*| and the fatigue coefficient k 3 of the rubber-modified gap-graded mixture has an adverse impact on its fatigue performance compared to that of the conventional gap-graded mixture.

Combined effect of compaction level and matric suction conditions on flexible pavement performance using construction and demolition waste

The characteristics of the unbound base layer have been recognized to influence the performance of flexible pavements to wide extents depending on climate conditions, construction quality, material source, traffic level, and pavement structure. Recently, unsaturated soil modeling has become generally accepted in predicting the pavement performance as pavement layers are typically placed well above soil water table, and tend to remain unsaturated during pavement service life. This paper investigates the combined impact of compaction level and initial matric suctions of construction and demolition (C&D) waste material used as a based layer on simulated pavement performance using the AASHTOWare Pavement ME Design software. Towards the preparation of the software inputs as per level 1 requirements, a laboratory experimental program was conducted on C&D material which includes the construction of soil water characteristic curve (SWCC) and determination of resilient modulus at four different moisture contents and two levels of compaction effort. The simulated pavement performance analyses consider two climatic conditions (dry and wet), two groundwater table levels (shallow and deep), two types of subgrade soil (strong and weak), and two thickness levels for the base and asphalt surface layers (thin and thick). Full statistical analyses of the main and interaction effects were performed on the results of AASHTOWare Pavement ME Design software. The results showed that the compaction level has more significant effect on the base and subgrade rutting and bottom-up fatigue cracking than the initial matric suction. In addition, both initial matric suction and SWCC input level were found to have a significant effect on all simulated distresses. Furthermore, the interaction between the compaction and initial matric suction was found to be significant.

Developing an Automated Technique to Calibrate the AASHTOWare Pavement ME Design Software

Many state highway agencies are in the process of implementing the AASHTOWare Pavement ME Design (PMED) software for routine pavement design. However, a recurring implementation challenge has been the need to locally calibrate the software to reflect an agency’s design and construction practices, materials, and climate. This study introduced a framework to automate the calibration processes of the PMED performance models. This automated technique can search PMED output files and identify relevant damages/distresses for a project on a particular date. After obtaining this damage/distress information, the technique conducts model verification with the global calibration factors. Transfer function coefficients are then automatically derived following an optimization technique and numerical measures of goodness-of-fit. An equivalence statistical testing approach is conducted to ensure predicted performance results are in agreement with the measured data. The automated technique allows users to select one of three sampling approaches: split sampling, jackknifing, or bootstrapping. Based on the sampling approach chosen, the automated technique provides the calibration coefficients or suitable ranges for the coefficients and shows the results graphically. Model bias, standard error, sum squared error, and p-value from the paired t-test are also reported to assess efficacy of the calibration process.

Development of Rutting Model for Indian Highways Based on Rut Depth Simulations from AASHTOWare Pavement ME Design Software

AbstractA majority of the approaches currently available for predicting rutting suggest limiting the vertical compressive strains on top of the subgrade in a pavement structure. Such approaches do ...

Limiting Strain Distribution Criteria for Perpetual Pavement Design Using AASHTOWare Pavement ME Design

Perpetual asphalt pavement designs have been based on controlling horizontal strains at the bottom of the asphalt layer and vertical strains on top of the subgrade to prevent bottom-up fatigue cracking and subgrade rutting, respectively. Traditionally, single strain thresholds had been used as limits where damage accumulation begins and propagates. The concept of strain distributions was introduced at the National Center for Asphalt Technology (NCAT), and it was found to better represent the wide response spectrum in asphalt pavements caused by the different loading and environmental conditions. This concept was developed based on information and data collected from the NCAT Pavement Test Track, and from this a limiting strain distribution was created to assist with perpetual pavement design. Several studies analyzed the criteria using pavement responses calculated from PerRoad predicted strains in Test Track sections and existing perpetual pavements. A limitation of the AASHTOWare Pavement ME Design software is its inability to output the pavement responses necessary for perpetual pavement design. The objective of this study was to analyze pavement response data predicted from an integration of the AASHTOWare Pavement ME Design software outputs and a JULEA based program developed at NCAT to create a limiting strain distribution for perpetual pavement design using the AASHTOWare Pavement ME Design software. Strains were calculated for Test Track sections using these tools and based on the results a limiting strain distribution was developed. This limiting strain distribution was then further evaluated using eight sections that won Perpetual Pavement Awards. Results showed that the horizontal strain distributions obtained from Test Track sections could differentiate the sections with cracking and the sections that did not crack. In the further evaluation, the horizontal strain distributions from the perpetual pavements did not exceed the limiting strain distribution developed from the Test Track sections, except for a section which surpassed it by a small margin at the 80th and higher percentiles. Vertical strains were also determined for these pavements and the current 200 microstrains at 50th percentile design criteria was met by all the sections.

Evaluation of four different climate sources on pavement mechanistic-empirical design and impact of surface shortwave radiation

ABSTRACT This paper compares the predicted distresses (via in the AASHTOWare Pavement ME Design software (PMED)) of asphalt concrete (AC) and jointed plain concrete pavement (JPCP) using four different climate data sources. These sources also include the Modern Era Retrospective Analysis for Research and Application (MERRA) Versions 1.0 and 2.0 (MERRA-1 and MERRA-2). Pavement performance predictions generated using these data showed disagreement among some of the climate data sources, especially for MERRA-2. Comprehensive diurnal and other time-series analyses of the raw climate data found significant disagreements in the percent sunshine estimates. Percent sunshine is used in the PMED environmental effects model to semi-empirically estimate the downwelling shortwave radiation reaching the pavement surface. Both MERRA data (MERRA -1 and MERRA-2) independently provide direct predictions of downwelling surface shortwave radiation (SSR). The direct model predictions of SSR were used to back calculate ‘synthetic’ per cent sunshine for input into the PMED. The use of the synthetic per cent sunshine derived from the predicted SSR eliminated nearly all discrepancies in the predicted pavement performance using MERRA-1 versus MERRA-2 data. Based on these results, the authors recommend that SSR rather than per cent sunshine be used as a direct input to the PMED.

Development of Structural Design Guidelines for Porous Asphalt Pavement

Porous asphalt pavements allow designers to introduce more sustainability into projects and lessen their environmental impact. Current design procedures are based primarily on hydrologic considerations; comparatively little attention has been paid to their structural design aspects. As their use grows, a design procedure and representative material structural properties are needed to ensure that porous pavements do not deteriorate excessively under traffic loads. The objective of this project was to develop a simple, easy to apply design procedure for the structural design of porous asphalt pavements. Two methodologies were considered for such a structural design procedure: ( a) the 1993 AASHTO Pavement Design Guide empirical approach, and ( b) the mechanistic–empirical approach employed by the AASHTOWare Pavement ME Design software. A multifactor evaluation indicated the empirical 1993 AASHTO design procedure to be the most appropriate platform at this time. It is noted, however, that both design procedures lack validation of porous asphalt pavements against field performance. AASHTO design parameters and associated material characteristics are recommended, based on an extensive literature review. For “thin” open-graded base structures (12 in. or less), the AASHTO procedure is performed as published in the 1993 Guide. For “thick” base structures (>12 in.), the base/subgrade combination is considered a composite system which supports the porous asphalt layer; an equivalent deflection-based approach is described to estimate the composite resilient modulus of the foundation system, prior to applying the 1993 AASHTO design procedure.

Mechanistic-Empirical design of perpetual pavement

Perpetual pavements use multiple, durable asphalt layers to produce a safe, smooth, long-lasting road. The pavement design begins with a strong, yet flexible bottom layer that resists tensile strain caused by traffic, and thus stops cracks from forming at the bottom of the pavement. Four perpetual pavement sections were designed and constructed in 2005 and currently are scheduled for rehabilitation for top-down surface cracking. These cracks have been confirmed by full-depth cores. This study revisited the design of these perpetual pavement sections using now available PerRoad and AASHTOWare Pavement ME Design software to investigate whether the design assumptions were correct. Fatigue lives of these sections were also evaluated based on bottom-up cracking. Layer moduli were backcalculated from the falling weight deflectometer (FWD) deflection data using the EVERCALC software. Tensile strains at the bottom of the asphalt layer were then computed. Results showed that predicted strain values derived from the mechanistic response models were lower than the tensile strains computed using moduli from the FWD deflection data. The required asphalt thickness from PerRoad was relatively higher than the asphalt thickness obtained from the AASHTOWare Pavement ME Design software over a 50-year design period. The study identified the most successful perpetual pavement design as the one with a rich bituminous mix in the base layer.

Approaches for local calibration of mechanistic-empirical pavement design guide joint faulting model: a case study of Ontario

ABSTRACT The Mechanistic-Empirical Pavement Design Guide (MEPDG) has been employed by agencies as an innovative method for pavement design since the National Cooperative Highway Research Program (NCHRP) Project 1-37A was implemented in 2004. Over the years, the MEPDG has evolved into the AASHTOWare Pavement ME Design software (AASHTOWare®). Local calibration of the performance models in the AASHTOWare® is a crucial and challenging task to improve the effectiveness of its application. The accuracy of the calibration depends on efficient methods and validation processes. This paper aims at developing local calibration methods for joint faulting prediction model of Jointed Plain Concrete Pavement (JPCP). This study not only focuses on improving the prediction accuracy of the joint faulting model but also demonstrating the various optimisation procedures in detail. A total of 27 representative JPCP sections were used in the processes of calibration. Three optimisation approaches were used: (1) One-At-a-Time (OAT) through the trial-and-error procedure, (2) generalised reduced gradient (GRG) using MS Excel® Solver, and (3) Levenberg-Marquardt Algorithm (LMA) fitting the functions. The prediction accuracy of local models was improved as compared with the global ones. Average Bias (AB) reduced from 0.3083 to 0.0578, and Standard Error of the Estimate (SEE) reduced from 0.3345 to 0.1912. Among the three local calibration approaches, approach 2 and approach 3 had more significant improvement on results than approach 1. Finally, the integral procedures were provided for local calibration in Ontario.

Effects of existing concrete pavement condition on performance of unbonded jointed plain concrete overlay

Abstract Unbonded concrete overlay (UBCO) is the most used pavement rehabilitation technique across United States with an overall usage of 47% amongst all the rehabilitation methods. It is aimed to improve the performance of any deteriorated/cracked jointed plain concrete pavement (JPCP). Unbonded JPCP overlay involves placement of a separation layer of hot mix asphalt (HMA), which acts as a stress relief layer between the existing concrete pavement and the overlay. There are numerous factors that affect the design and performance of UBCOs and out of these, existing pavement condition or the severity of damage of existing pavement is a prime factor. The severity of damage is described by the distressed elastic modulus thus, accurate determination of the distressed elastic modulus of the existing concrete pavement is essential for predicting the accurate performance of the unbonded overlay. This study focuses on analyzing the impact of distressed modulus by conducting simulations in the AASHTOWare pavement ME design software version 2.3 and evaluating the predicted performance of JPCP overlay for two different climatic regions. The results indicated that the distressed modulus of existing concrete pavement affects the performance of the overlay with regards to transverse cracking, joint faulting and pavement roughness. Transverse cracking is the most affected performance parameter with a change of 0.27%–2.31% with a unit change in distressed modulus. The impact of climatic conditions on the performance of unbonded overlay was also observed. The adverse effects of distressed modulus can be minimized by reducing the joint spacing or increasing the overlay slab thickness.

Spatial variability of compacted aggregate bases

Abstract This paper evaluates the construction quality of aggregate base course layers in terms of the variability and uniformity in density and modulus based measurements. Field and laboratory tests were conducted on 10 aggregate base course layers during HMA pavement construction in Wisconsin. Field tests consisted of in-place unit weight, LWD, DCP, and Stiffness Gauge measurement while laboratory tests included particle size analysis, compaction test, and repeated load triaxial test. Moreover, sensitivity analysis was conducted to assess the influence of the base course layer input parameters on the long-term performance of HMA pavements using the AASHTOWare Pavement ME Design software. Field and laboratory test results demonstrated the existence of high spatial variability in both density (relative compaction ranged from 82.6 to 109.1%, with 17% of test points having values

Relative Comparison of Complex Dynamic Modulus Predictive Models for Non-Conventional Asphalt Concrete Mixtures

Abstract Because of the widespread use of additives, a revised dynamic modulus (|E*|) predictive approach is needed for the mechanistic–empirical analysis of asphalt pavement designs. The importance of predicting |E*| relates to its use as a sensitive input in the AASHTO Pavement ME Design software. The objective of this study is to evaluate two |E*| predictive models currently used for asphalt mixtures that include non-conventional additives, and to provide recommendations for enhancing prediction capability of the models when these types of materials are used. The focus of the paper is on finding ways to efficiently and accurately generate |E*| inputs for the software when actual pavement response is not measured. Impacts of mixture type, temperature, and binder grade on |E*| predictions are explored. The current software uses three levels of inputs, two of which require key material characteristics to predict |E*| values rather than employing laboratory-measured |E*|. This study shows that for non-conventional mixtures, 53 % of |E*| values predicted by the 2006 Witczak predictive equation (WPE) are greater than values predicted by the 1999 WPE. This trend of over-prediction is observed at both low and high test temperatures. However, the opposite effect exists between the two WPEs at intermediate test temperatures. This research shows that adjusting the original binder type of non-conventional mixtures provides a significant improvement in predictive accuracy for |E*|. The findings of this study provide suggestions for alterations to binders, to adjust the WPE model’s terms for better predictive accuracy, and supplies recommendations to practitioners who use the AASHTOWare Pavement ME Design software; however, it is still evident that the laboratory measurement of |E*| values is still the preferred approach for generating inputs for the software.

Calibration and sensitivity analysis of rut prediction model for semi-rigid pavement using AASHTOWare ME design

Rutting is one of the most serious distresses of semi-rigid asphalt pavements in Jiangsu. In this research, AASHTOWare pavement ME Design software was used for rutting prediction of semi-rigid pavements. A semi-rigid pavement is composed of a flexible layer and a rigid layer. Local calibration was done first by taking into account local materials, traffic information, and environmental conditions. A total of eight sites representing typical mixture types of Jiangsu province were selected to complete the calibration and another four highways were chosen to make the validation. Then the calibrated software was used to identify sensitive factors for rutting prediction. Critical inputs needed for the calibration and sensitive analysis were tested or collected from local project-level Pavement Management System (PMS) database. The modulus of semi-rigid base was back-calculated from deflection basin data. Calibration coefficients for each typical structure and the optimal coefficients for this region were identified, respectively. Results also demonstrate that traffic inputs and thickness of Hot Mixed Asphalt (HMA) layers are more sensitive to the predicted rutting depth than void contents of HMA mixtures.