Pavement Deterioration Research Articles

Subgrade performance assessment for rigid runway using long-term pavement performance database

Maintaining desired subgrade performance is an effective way to reduce runway pavement deterioration. Due to lack of extensive field test data, life-cycle performance of runway subgrade has not been fully understood. In order to quantitatively estimate subgrade condition, a novel method of evaluating subgrade performance was developed and validated using the 726 sets of Heavy Weight Deflectometer (HWD) test data of ten runway sections. Statistical analysis demonstrates that the structural behaviour of rigid runway subgrade follows normal distribution in different service stages and can be efficiently evaluated by the subgrade performance index (ψ). The results of factor analysis show that Accumulated Air Traffic Volume (ATV) during service life is the major cause of spatial variations in subgrade condition. In the designed service period of runway, it validates that sea-reclaimed subgrade results in faster degradation in the initial stage of service life while thicker pavement exhibits better capability in protecting the subgrade soil in long-term view. Besides, the differences in applied loads and pavement thickness give rise to the subgrade performance variation in longitudinal direction. Meanwhile, the comparison between the main and the less trafficked test lines in transversal direction reveals that the aircraft impacts play a positive role in resisting the natural fatigue process. By the suggested method, subgrade performance of HWD test points can be categorized into 4 levels from “Excellent”, “Good”, “Fair” to “Poor” based on ψ value. It is helpful for airport agency to make scientific decisions on Maintenance and Rehabilitation (M&R) treatment by calculating the effective area of envelope (β) using the ratio of subgrade performance (η).

Long-Term Mechanical Deterioration Trends and Mechanisms of SBS-Modified Asphalt Mixtures

Understanding the long-term performance deterioration trends and mechanisms of asphalt pavement is crucial for effective maintenance strategies. This study characterizes and correlates the multi-scale performance deterioration of a 14-year asphalt pavement. Air void measurements, indirect tensile (IDT) fatigue testing, Fourier transform infrared spectroscopy (FTIR), and dynamic shear rheometer (DSR) testing were conducted on pavement cores and recovered binder. Multiple regression analysis was then performed on various performance indicators. Laboratory results indicate that the chemical composition and viscoelastic properties of SBS-modified binders evolve rapidly in the first few years, followed by a relatively stable aging rate. After 14 years, the mechanical and rheological properties of lower-layer mixtures deteriorate to a similar degree as the surface layer. Correlation analysis revealed that the residual strength of the mixture is more influenced by air voids, while reductions in fatigue life are primarily driven by binder aging. These findings highlight the necessity of applying preventive maintenance within the first 3–5 years to rejuvenate the surface asphalt and rehabilitate both the surface and underlying layers after long-term service.

Utility Cut Impact Assessment and Fee Development Using Pavement Management System

The purpose of this study is to estimate any damage caused by utility cuts to pavements and develop a fee schedule to recover the costs associated with such damage using the City of Pacifica, CA, U.S.’s pavement management system (PMS). To accomplish this, the study looked at the functional deterioration of pavements resulting from utility cuts. The City of Pacifica’s PMS containing a vast dataset of pavement distress spanning 15 years, comprising thousands of data points encompassing various pavement ages and conditions, was analyzed to assess the impact of utility cuts. The findings from this study include: 1) Pavements with cuts of any size deteriorate more than pavements without cuts across all age groups with one exception for older residentials with small cuts; 2) On average, pavement condition index drops by 30% if the cut area is greater than 10% of the section area; and 3) Utility cuts inflict greater damage on newer pavements (<10 years old) compared with older ones (≥10 years old). Consequently, new pavements experience an average percent reduction of approximately 33% in their remaining service life, while older pavements suffer a reduction of about 17%. The statistical analyses indicate that utility cuts caused significant damage, and supported a tiered utility cut fee structure based on functional classification, age of pavement, and size of the cut. The resulting fee schedule is based on 2021 material and construction cost estimates; consequently, implementation including an annual adjustment for inflation is recommended. Example fee calculations are provided.

Nanomaterials in asphalt cement: Exploring their single and combined effects on the physical and rheological properties

Pavement deterioration due to rutting, fatigue, and thermal cracking poses significant challenges to road infrastructure. Traditional asphalt modifiers often fall short in addressing these issues, leading to growing interest in advanced materials such as nanomaterials. This study investigates the individual and combined effects of three nanomaterials: nano-titanium dioxide (NT), nano-alumina (NA), and nano-silica (NS), on the physical and rheological properties of asphalt binders when used in dosages of 0%, 1%, and 2% by the weight of asphalt. This study aims to enhance asphalt performance and contribute to international research efforts focused on pavement durability. The experimental program evaluated the penetration, softening point, mass loss after aging, and viscosity properties, in addition to rutting and fatigue resistance through dynamic shear rheometer (DSR) tests. Scanning electron microscopy (SEM) was also employed to observe morphological changes. Results showed that 2% NA reduced penetration by 3.19%, while 2% NS increased the softening point by 2.41%. The combination of NA and NS had the highest effect on the softening point (F = 6.21, p = 0.008). NA and NT reduced mass loss, with 2% NA lowering it from 0.432% to 0.201%. Viscosity increased by 17.4% with 2% NA, while the NA and NS combination had the most significant overall impact (F = 44.78, p = 0.000). At higher temperatures, 2% NA was the most effective in reducing aging. Optimizing the use of NA and NS, either individually or combined, offers the best improvements in binder stiffness, thermal stability, and aging resistance.

Glass fiber waste as a potential bitumen modifier and stabilizing agent in asphalt mixture.

The deterioration of Malaysia's flexible road pavements due to rutting and moisture damage presents a critical problem. Meanwhile, disposing of glass fiber wastes from manufacturing process further worsens environmental concerns. This research explores the feasibility of using glass fiber wastes as bitumen modifiers and stabilizers in stone mastic asphalt (SMA). The performance of SMA14 incorporating glass fiber waste using wet method and dry method were compared in this study. Bitumen 60/70 PEN was modified with varying percentages of glass fiber waste namely, 0.5%, 1.0%, 1.5%, and 2.0% by weight of bitumen. The SMA14 mixture was modified with glass fiber waste at 0.3% by the weight of total mixture. The physical and rheological characteristic of modified bitumen binder were assessed using penetration, softening point, storage stability, viscosity, and dynamic shear rheometer (DSR) tests. The Marshall properties and performance of the SMA14 mixture incorporating glass fiber waste were evaluated. The findings demonstrate that glass fiber waste-modified bitumen exhibits enhanced penetration, softening point, viscosity, and rutting resistance compared to the unmodified sample. Adding glass fiber waste using dry method shows significant resistance to abrasion and rutting and demonstrates higher indirect tensile strength and TSR value.

Macroscopic State-Level Analysis of Pavement Roughness Using Time–Space Econometric Modeling Methods

This paper used pavement condition data collected by the Federal Highway Administration (FHWA) between 2001 and 2006 aggregated by U.S. states to identify macroscopic factors affecting pavement roughness in time and space. To account for prior pavement conditions and preservation expenditure over time, time autocorrelation parameters were introduced in a spatial modeling scheme that accounted for spatial autocorrelation and heterogeneity. The proposed framework accommodates data aggregation in network-level pavement deterioration models. Because pavement roughness across different roadway classes is anticipated to be affected by different explanatory parameters, separate time–space models are estimated for nine roadway classes (rural interstate roads, rural collectors, urban minor arterials, urban principal arterials, and other freeways). The best model specifications revealed that different time–space models were appropriate for pavement performance modeling across the different roadway classes. Factors that were found to affect state-level pavement roughness in time and space included preservation expenditure, predominant soil type, and predominant climatic conditions. The results have the potential to assist governmental agencies in planning effectively for pavement preservation programs at a macroscopic level.

Machine learning modelling the rut depth of WMA mixtures with variable reclaimed asphalt pavement (RAP) and foamed bitumen content

ntroduction. Rutting of flexible, super flexible and semi-rigid pavement structures is a typical and frequently decisive condition parameter, form of pavement deterioration. That is why, any research result in the field can have of high importance for the road engineers. Problem Statement Rutting poses a significant challenge to asphalt pavements, causing permanent deformation under heavy loads, particularly in warm and wet conditions. Purpose. This pavement distress type has — in addition to riding comfort challenges — important traffic safety consequences (e.g. aquaplaning), as well. The research work concentrates on the influence of the use of warm mix asphalt, reclaimed asphalt material and foamed bitumen binder on the rut depth of asphalt pavements.

Analytical Investigation of Fatigue Behavior in a Modified Composite Steel Box Concrete Girder Bridge with Corrugated Steel Webs under Pavement and Expansion Joint Deterioration

Analytical Investigation of Fatigue Behavior in a Modified Composite Steel Box Concrete Girder Bridge with Corrugated Steel Webs under Pavement and Expansion Joint Deterioration

Fiber Showdown: A Comparative Analysis of Glass vs. Polypropylene Fibers in Hot-Mix Asphalt Fracture Resistance

Cracks in asphalt mixtures compromise the structural integrity of roads, increase maintenance costs, and shorten pavement lifespan. These cracks allow for water infiltration, accelerating pavement deterioration and jeopardizing vehicle safety. This research aims to evaluate the impact of synthetic fibers, specifically glass fiber (GF) and polypropylene fiber (PPF), on the crack resistance of Hot-Mix Asphalt (HMA). An optimal asphalt binder content of 5% was used in all sample designs. Using the dry mixing technique, GFs and PPFs were incorporated into the HMA at dosages of 0.50%, 1.00%, and 1.50% by weight of the aggregate. The effects of these fibers on the mechanical fracture properties of the HMA were assessed using Semi-Circular Bending (SCB), Indirect Tensile Asphalt Cracking Tests (IDEAL-CTs), and Three-Point Bending (3-PB) tests. This study focused on fracture parameters such as fracture work, peak load, fracture energy, and crack indices, including the Flexibility Index (FI) and Crack Resistance Index (CRI). The results from the SCB and IDEAL-CT tests showed that increasing GF content from 0.5% to 1.5% significantly enhances the flexibility and crack resistance of HMA, with FI, CRI, and CT Index values increasing by 247.5%, 55%, and 101.35%, respectively. Conversely, increasing PPF content increases the mixture’s stiffness and reduces its crack resistance. The PP-1 mixture exhibited higher FI and CT Index values, with increases of 31.1% and 10%, respectively, compared to the PP-0.5 mixture, based on SCB and IDEAL-CT test results. The SCB, IDEAL-CT, and 3-PB test results concluded that fibers significantly influence the fracture properties of bituminous mixtures, with a 1% reinforcement dosage of both PPFs and GFs being optimal for enhancing performance across various applications.

Enhancing adhesive interlayer performance with waste tire rubber and amorphous poly alpha olefin compound modified asphalt

Insufficient bonding performance in interlayers is a key factor in the deterioration of bridge deck pavements. This study evaluates the bonding and durability of Waste Tire Rubber (WTR)/Amorphous Poly Alpha Olefin (APAO) modified asphalt compared to the commonly used Styrene-Butadiene-Styrene (SBS) modified asphalt. We conducted shear and pull tests to analyze how different bonding processes and the texture depth of the concrete surface affect bonding performance. The research also assessed the durability of the adhesive layer under conditions such as temperature fluctuations, water immersion, and aging. Results show that the choice of bonding method significantly impacts adhesive performance, with the coating bond method being superior to the crushed stone bond method. A concrete surface texture depth of 0.88 mm was identified as optimal for improving adhesive performance. Moreover, the WTR/APAO adhesive interlayer provided better adhesive and durability performance than the SBS adhesive interlayer under conditions of temperature fluctuations and water immersion. Based on these findings, the study recommends using the coating bond process and 15%WTR + 4%APAO modified asphalt for the adhesive interlayer.

Study on the influence of tire polishing on surface texture durability and skid resistance deterioration of asphalt pavement

As an inherent attribute of asphalt pavement, texture durability is the essential reason for the change in skid resistance. However, different scale texture deterioration behavior remains unclear by tire wearing at present. To explore the influence of the durability of multi-scaled textures on skid resistance, nine pavement specimens were tested using the Harbin polishing and dynamic friction integrated experimental machine (HPFM). The pavement anti-skid texture tester (PATT-II) was used for high-precision texture scanning and reconstruction. The results show that the texture richness and skid resistance of the three types of pavements in 300 min polishing are ranked as Open-graded Friction Coarse (OGFC) > Stone Mastic Asphalt (SMA) > Asphalt Concrete (AC), while SMA presents the best durability, determined by the material skeleton structure of asphalt mixture. The macro-texture deterioration occurs slightly at first and then tends to stabilize in 300 min polishing. The micro-texture deterioration behavior is the same as the μHPFM, increasing rapidly at the beginning, then slowly decreasing, and finally remaining constant. This deterioration is caused by the asphalt damage and continuously wearing aggregate surface. The 2D-PSD deterioration behavior is more significant with a smaller texture scale in 300min polishing, and the most considerable contribution wavelength in the microscopic scale range is 0.15 mm–0.3 mm, which is determined by the adhesion characteristics and molecular mechanism between a mineral mixture and asphalt material. The influence of pavement texture on the dynamic friction coefficient is significantly different under different water film thicknesses, the micro-texture and macro-texture play the main roles in boundary and mixed lubrication, respectively.

Characteristics of life-cycle carbon dioxide emissions of arterial highway maintenance and the influencing factors

With the focus of highway development transitioning from construction to maintenance, a comprehensive understanding of the characteristics and influencing factors of carbon dioxide (CO2) emissions from highway maintenance activities is crucial for formulating effective strategies to promote the low-carbon development of road infrastructure. However, the quantitative relationships between CO2 emissions from highway maintenance schemes and factors such as pavement deterioration, traffic volume, and road grade remain unclear owing to a lack of comprehensive, multi-category, and real data. Using real maintenance data from 340 arterial highway segments in China, this study conducts the life cycle assessment (LCA) to estimate CO2 emissions from maintenance activities and examines the primary emission sources among various structural layers and materials. Furthermore, multiple linear regression (MLR) analysis is conducted to investigate the impact of traffic volume, road grade, and pavement deterioration on CO2 emissions from maintenance projects, and factors influencing the early-stage degradation of pavement performance. The results demonstrate that average CO2 emissions from heavy rehabilitation projects are 6.97 times higher than those from medium rehabilitation projects. Emissions from heavy rehabilitation projects exhibit a significantly negative linear relationship with the riding quality index (RQI) before maintenance (p < 0.05), and emissions from medium rehabilitation projects show a significant negative linear relationship with the pavement condition index (PCI) before maintenance (p < 0.05). Emissions from heavy and medium rehabilitation projects are significantly positively correlated with heavy vehicle traffic volume before maintenance (p < 0.05). Moreover, the early-stage degradation of PCI after heavy rehabilitation and RQI after medium rehabilitation exhibit significantly negative linear relationships with their respective indicators before maintenance (p < 0.05). The early-stage degradation of RQI after heavy rehabilitation is significantly positively correlated with CO2 emissions from the base course and cushion layers (p < 0.05). The findings emphasize that timely maintenance and reduction of CO2 emissions from asphalt mixing equipment are essential for mitigating emissions from road maintenance. This study offers valuable insights for advancing the low-carbon development of highways in temperate regions.

Assessing Multifaceted Effects of Speed Humps and Bumps: Travel Time, Safety, and Environmental Considerations

This study focuses on investigating the significant impacts of speed breakers on various parameters, including travel time delays, vehicle speeds, fuel consumption, pavement maintenance costs, and vehicular exhaust emissions. Field data was collected and analyzed to assess the effects of different types of traffic calming measures on these parameters. The findings provide valuable insights into the implications of speed breakers on road safety, environmental pollution, and overall road infrastructure management. The results reveal that the implementation of speed humps, speed bumps, and triple bumps effectively slows down vehicles, as evidenced by considerable reductions in the 85th percentile speeds. The reduction percentages were 41.65% for speed humps, 73.52% for speed bumps, and 86.27% for triple bumps. This indicates the effectiveness of these traffic calming measures in improving road safety by reducing vehicle speeds. However, the presence of speed breakers also leads to increased travel time delays. On average, traversing stretches with speed humps, speed bumps, and triple bumps resulted in delays of 9.31, 16.42, and 29.51 seconds, respectively. While the individual delay times may appear relatively short, the cumulative effect of multiple speed obstacles along a road needs to be considered. Another significant impact observed is the increased fuel consumption associated with speed breakers. The study found that for every 100 km of travel, motorcycles and passenger cars consumed approximately 12.07 km and 27.37 km of additional fuel, respectively, when the density of speed breakers was 1.33/km. This translates to a fuel consumption increase of 13.73% for motorcycles and 37.74% for passenger cars. Furthermore, the presence of speed humps was found to contribute to pavement deterioration, as indicated by decreased Pavement Condition Index (PCI) values. The study also revealed that sections with speed humps incurred significantly higher maintenance costs compared to sections without speed humps. The increase in maintenance cost ranged from 100 to 264% across different road sections, with higher traffic volumes leading to greater cost escalation. Additionally, the study confirms that lower vehicle speeds, particularly between 0-15 km/hr, are associated with higher emissions of pollutants, including carbon monoxide (CO) and other pollutants. This highlights the environmental implications of speed breakers and their contribution to urban air pollution. Doi: 10.28991/CEJ-2024-010-07-07 Full Text: PDF

Recovering the properties of aged bitumen using bio-rejuvenators derived from municipal wastes

Ageing of bitumen leads to significant performance deterioration of asphalt pavements and leads to material properties that are not conducive to recycling. Aiming to maximise the reusability of bitumen, this study investigated the feasibility of rejuvenating aged bitumen using bio-based rejuvenators synthesised from municipal wastes. Two bio-rejuvenators were used in this study, namely Rej-A which was a crude polymer with bio-waste pyrolysis dense fractions and Rej-B which was a filtered pyrolysis wax further derived from Rej-A. The bio-rejuvenators, virgin, aged, and rejuvenated bitumen were characterised using a comprehensive testing programme of gas chromatography and mass spectrometry (GC-MS), Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), multiple stress creep and recovery (MSCR), linear amplitude sweep (LAS), and frequency sweep tests. It was observed that both bio-rejuvenators produced in this study can effectively recover the rheological properties of aged bitumen, improving its fatigue performance, e.g. the fatigue lives (at 15 % strain level) of Rej-A and Rej-B rejuvenated bitumen were 5.4 times and 3.0 times of that for aged bitumen when the dosage was 14 %. The rejuvenated bitumen was more sensitive to strain while less sensitive to temperature compared with virgin bitumen. Overall, Rej-A outperformed Rej-B in recovering the properties of aged bitumen. However, Rej-A was thermally unstable, undergoing 15.6 % mass loss when heated to 160 °C.

Fuzzy Rule Based System of Optimal Pavement Maintenance and Rehabilitation Strategies for Yangon-Mandalay Expressway

Purpose: Systematic pavement management plays a vital role in the better Road Asset Management system. The lifespan of pavement can be preserved and prolonged by adequate maintenance measures in proper time. By early detection and repair of defects at initial stages with predictive maintenance reduces the rapid deterioration of the pavement. Moreover, inaccuracy in pavement deterioration prediction leads to an improper maintenance with wastage of time, cost and labor strength. To overcome all of these obstacles, this paper attempts an approach on optimal pavement maintenance strategy by means of fuzzy rule-based system. Materials and Methods: In this research, four pavement indicators of PCI, IRI, PSR and PSI have been taken into account as antecedents and five different types of pavement maintenance as consequents. In this research, ASTM D-6433, Road Lab Pro software, AASHTO guidelines and Fuzzy Logic (Mamdani) model have been used to evaluate the current pavement condition and optimal pavement maintenance strategies. Findings: According to research area, 130 total pavement sample units were undertaken to study for the mean pavement condition of PCI value 54.93 (poor), IRI 7.01 (fair), PSR 3.33 (fair) and PSI 3.35 (fair). Due to 13 years-old life span of traffic volume, temperature and other external factors, this expressway is suffering from potholes, bleeding, longitudinal and transverse cracking, weathering, joint reflection cracking for Asphalt Concrete (AC) overlay and linear cracking, joint seal failure, scaling, faulting, depression, lane/shoulder drop off for existing concrete pavement. According to the fuzzy logic model results, 42 numbers of fuzzy If-Then maintenance rules were verified as the most relevant pavement maintenance and rehabilitation strategies for Yangon-Mandalay Expressway. Implications to Theory, Practice and Policy: This research provide implications to the study and contributions to theory, practice and policy. This research paper insights into effective infrastructure maintenance and investment, emphasizing the role of advanced computational techniques in transportation economics. The key advantage of this research paper is to be effective, supportive, easy and accessible decision-making tool for transportation and pavement engineers, expressway planners and highways department authorities especially from developing countries.

Bridging multi-level vehicle behavioural patterns with long-term pavement condition: a bidirectional modelling approach for progressively mixed autonomous traffic flow

The increasing of AVs’ market penetration rate (MPR) changes the traffic behavioural pattern and ultimately influences pavement. Pavement condition, in turn, influences microscopic behaviours. The above bidirection influencing mechanism has not been investigated fully yet. This research fill this gap by modelling the linkage between multi-level microscopic behaviour and pavement sustainability. Three levels of behaviour are considered: travel behaviour, microscopic traffic behaviour, and driving behaviour. The latter two are modelled using stochastic lateral movement model, while the former one is captured by a mixed autonomous traffic assignment model. Microscopic behaviours’ influence on pavement is described by a data-driven model, while the reverse counterpart is described by connecting pavement condition with link wandering and disutility. Our analysis results reveal that at link level, AVs can cause extra 50% drop in free flow speed due to pavement deterioration. Neglecting pavement evolution in strategic assignments leads to a 0.2% increase in network cost.

Impacts of heavy-duty electric trucks on flexible pavements

ABSTRACT The transportation sector is responsible for significant greenhouse gas (GHG) emissions, with medium- and heavy-duty trucks (MHDTs) being major contributors. In response, medium- and heavy-duty electric trucks (MHDETs) are being explored as zero-emission alternatives. However, the weight of high-capacity batteries needed for long-haul trips and heavy loads could increase the axle loads as well as the gross vehicle weight (GVW) of heavy-duty electric trucks (HDETs), leading to extra damage on flexible highway pavements. This study simulated the GVW increment of HDETs and assessed its effects on pavement damage, environmental impacts, and life-cycle costs of four typical highway pavement structures in Illinois (known as thick–weak, thick–strong, thin–weak, and thin–strong). The utilisation of electric trucks resulted in significant reductions in diesel combustion related global warming potential (GWP) emissions and costs (in $2022) by 73% and 11.5%, respectively. However, the results demonstrated that with a 100% penetration of HDETs carrying an additional weight of 8 kips per truck, the pavement deterioration accelerated compared to traffic with conventional trucks. As a consequence, GWP and costs were reduced by 69% and 10.6%, respectively.

Concrete Highway Crack Detection Based on Visible Light and Infrared Silicate Spectrum Image Fusion.

Cracks provide the earliest and most immediate visual response to structural deterioration of asphalt pavements. Most of the current methods for crack detection are based on visible light sensors and convolutional neural networks. However, such an approach obviously limits the detection to daytime and good lighting conditions. Therefore, this paper proposes a crack detection technique cross-modal feature alignment of YOLOV5 based on visible and infrared images. The infrared spectrum characteristics of silicate concrete can be an important supplement. The adaptive illumination-aware weight generation module is introduced to compute illumination probability to guide the training of the fusion network. In order to alleviate the problem of weak alignment of the multi-scale feature map, the FA-BIFPN feature pyramid module is proposed. The parallel structure of a dual backbone network takes 40% less time to train than a single backbone network. As determined through validation on FLIR, LLVIP, and VEDAI bimodal datasets, the fused images have more stable performance compared to the visible images. In addition, the detector proposed in this paper surpasses the current advanced YOLOV5 unimodal detector and CFT cross-modal fusion module. In the publicly available bimodal road crack dataset, our method is able to detect cracks of 5 pixels with 98.3% accuracy under weak illumination.

Ensemble Learning Approach for Developing Performance Models of Flexible Pavement

This research utilizes the Long-Term Pavement Performance database, focusing on devel-oping a predictive model for flexible pavement performance in the Southern United States. Analyzing 367 pavement sections, this study investigates crucial factors influencing asphaltic concrete (AC) pavement deterioration, such as structural and material components, air voids, compaction density, temperature at laydown, traffic load, precipitation, and freeze–thaw cycles. The objective of this study is to develop a predictive machine learning model for AC pavement wheel path cracking (WpCrAr) and the age at which cracking initiates (WpCrAr) as performance indicators. This study thoroughly investigated three ensemble machine learning models, including random forest, extremely randomized trees (ETR), and extreme gradient boosting (XGBoost). It was observed that XGBoost, optimized using Bayesian methods, emerged as the most effective among the evaluated models, demonstrating good predictive accuracy, with an R2 of 0.79 for WpCrAr and 0.92 for AgeCrack and mean absolute errors of 1.07 and 0.74, respectively. The most important features influencing crack initiation and progression were identified, including equivalent single axle load (ESAL), pavement age, number of layers, precipitation, and freeze–thaw cycles. This paper also showed the impact of pavement material combinations for base and subgrade layers on the delay of crack initiation.

Reliability-Based Pavement Roughness Progression Modeling Using Bayesian Approach

This paper aims to develop reliability-based roughness progression models for bituminous pavements across different climatic zones in India. The methodology involves dividing the Indian geographical region into six climatic zones with specific climatic characteristics that influence pavement deterioration. This delineation is achieved using K-means clustering and considers parameters such as temperature, rainfall, and humidity. The roughness progression models and reliability interpretations are developed through a Bayesian regression framework. Initially, International Roughness Index (IRI) progression models are created for three climatic zones: hot and dry, warm and humid, and moderate. These models are based on time series data from 2015 to 2016, gathered from 130 pavement sections in each zone. To validate the models, additional time series data from 2016 to 2017 are utilized. The forecast results indicate that the hot and dry zone exhibits the highest IRI progression rate for specified causal variable values, followed by the warm and humid zone and the moderate zone. The adoption of the Bayesian regression framework provides probabilistic parameter distributions for model coefficients, enabling the assessment of model-level reliability. The study demonstrates that, by adjusting the quartile of causal variables, the overall reliability of the model can be improved, thereby reducing the deviation from actual IRI values. Moreover, it is possible to evaluate variable-level reliability by examining the influence of individual variables on roughness progression.