Pavements in tropical regions are affected by high temperatures and ageing, and are susceptible to rutting, which reduces their resilience and durability. Hence, this study investigates the modification of bitumen with Styrene–Butadiene Rubber (SBR) at 0%, 3%, 6%, and 9% by weight. Conventional tests showed that SBR modification improved high-temperature properties up to 6%, followed by a sudden reduction at 9% modification, as evidenced by increased softening point and reduced penetration. At 6% modification, the SBR-modified bitumen would remain uniform and stable during storage. It would not affect performance upon use after storage, demonstrating its suitability as a performance-enhancing polymer for hot-climate applications. Multiple Stress Creep Recovery (MSCR) testing shows reductions in non-recoverable creep compliance and enhanced elastic recovery, making the modified bitumen. The 6% SBR modified binder showed a significantly higher Jnr diff value with a Jnr diff value of 53.42%. Similarly, the SBR-modified binders showed improved recovery, with %R 0.1 values of 14.89% to 18.45% at 64 °C and %R 3.2 values of 0.32% to 1.71%. Linear Amplitude Sweep (LAS) results showed that a 9% modification yielded the highest N_f value, but beyond 6%, the improvement was negligible. Considering cost and optimal performance, 6% SBR content modification should be considered. Glover–Rowe parameters showed that SBR-modified binders retained their elasticity and reduced the brittleness of bitumen, unlike unmodified binders, which shifted towards brittle behaviour. Pearson correlation analysis shows a strong positive cluster among fatigue life, % recovery, Fail Temperature (Unaged and Aged), G*/sin δ, softening point, elastic recovery, and rutting parameters, with correlation values exceeding 0.90 in most cases. Grey Relational Analysis (GRA) shows that a 6% SBR with a Grey Relational Grade (GRG) of 0.843 was ranked highest among all modifications. Principal Component Analysis (PCA) shows that a 6% SBR modification of the bitumen is optimal, providing a balance among rutting resistance, fatigue performance, and ageing durability. These findings highlight the potential of SBR-modified bitumen to enhance pavement performance and service life in tropical climates.

Accurate prediction of rolling resistance (RR) is essential for improving vehicle fuel efficiency and supporting policymakers in making sustainable environmental decisions. This study introduces a novel framework that integrates both data-driven and physics-based approaches to enhance RR prediction by incorporating tire-penetration level indicator, the Delta (δ) parameter. The research investigates the relationships between RR, the δ parameter, and texture properties to refine predictive modelling. A portable device was built to measure the in-field δ parameter using tire-pavement interaction. Machine learning (ML) techniques, including multiple linear regression (MLR), random forest regressor (RFR), artificial neural networks (ANN) and finite element method-based (FEM) tire-pavement interaction models were employed to develop and validate the framework. Findings from the FEM tire-pavement interaction model confirmed the reliability of the δ parameter. Exploratory data analysis (EDA) highlighted the strong correlation between texture metrices such as MPD, ETD, and RMS, reinforcing the δ parameter's role in tire-pavement interactions. Comparative analysis of different pavement surfaces revealed that worn surfaces contribute to higher δ parameter values and increased RR. The improvement resulting from the inclusion of the δ parameter is particularly evident in the ANN and RF models, confirming nonlinear interaction effects between tire penetration and surface texture. It was also observed that the obtained RR data follow a non-normal distribution, which most of the previous studies did not consider. A deeper statistical insight showed that the δ parameter has a significant impact on RRC prediction. The primary contribution of this study lies in demonstrating the feasibility of integrating a physics-based tire-pavement interaction parameter into ML models for rolling resistance prediction, thereby bridging mechanistic modelling and machine learning within pavement engineering.

A major contributor to GHG emissions is the transportation sector, particularly pavement transport. The limited understanding of tire-pavement interactions leads to inaccurate predictions of these emissions, particularly from rolling resistance (RR). Traditional methods for predicting RR are constrained by their limited applicability and inability to account for the complex dynamics of tire-pavement interactions, resulting in poor prediction accuracy. These limitations make it challenging for policymakers to make proper decisions, as existing methods are manual and labour-intensive. This study aims to develop an automated system to capture tire-pavement interaction data using the Laser Crack Measurement System (LCMS). To the best of the authors' knowledge, no robust technique currently exists for automatically calculating tire penetration-related information from LCMS data to predict RR. Therefore, this research explores machine learning (ML)-based models to reduce uncertainties in existing approaches and enhance RR predictions using automated LCMS data. It examines the relationships between RR, tire penetration volume, and the characteristics of the Dutch pavement network, comparing the results with those of commonly used RR prediction models. The study introduces an automatic tire penetration calculation approach using LCMS data to assess the impact of tire penetration volume and depth on RR in relation to surface properties. The findings reveal that traditional empirical models show poor correlations between RR and texture indicators, whereas ML-based models significantly improve the accuracy of RR predictions. These results could inform the development of strategies to reduce GHG emissions from pavement transport, supporting global efforts to combat climate change and achieve the goals of the Paris Agreement.

Emulsion-treated aggregate base layer structure is one of the popular choices to form a more stabilized layer, in which aggregates are treated with slow-setting bitumen emulsion. The aim of the study is to propose a three-dimensional finite element model that is capable of showing the potential benefits of using an emulsion-treated aggregate layer. The damaging effect of overloading and high temperature in a tropical climatic condition on the pavement response have been highlighted in this study. The analyses showed that by using an emulsion-treated aggregate layer, the rut resistance and fatigue life considerably improve.

The design of asphalt pavement in many developing nations still relies on an empirical approach, often leading to either premature failure of the pavement or overdesign. The transition from an empirical approach to semi-mechanistic or mechanistic was felt by past researchers, and many advanced tools based on these approaches have been developed. Computational tools, like finite element (FE) analysis, are capable of handling complex material properties of pavement materials under nonuniform loading conditions. Asphalt mixes are widely known to exhibit viscoelastic behaviour based on temperature and loading conditions, while the response of unbound materials under cyclic loading is stress dependent. Due to the complexity of the entire process, numerous pavement design tools treat them as purely elastic materials. This study aims to develop a finite element based, simple, and practical framework to assess the structural response of asphalt pavement under overloading and varying temperature conditions in a tropical climate. The framework offers a straightforward method for the determination of time dependent viscoelastic parameters of the asphalt mixture using creep compliance test. The nonlinear stress-dependent behaviour of unbound granular materials (UGMs) in different layers has also been presented based on repeated load triaxial compression testing. It was concluded that overloading and increasing mix temperature severely affect pavement performance. A 25 % overloading resulted in a reduction of subgrade rutting life by 62.33 %, whereas an increase in mix temperature by 10° C at intermediate temperature reduced asphalt fatigue life by 29.34 % and subgrade rutting life by 42.03 %.

In most of developing countries across the world, pavement design is still based on an empirical approach that may result in premature failure or overdesigned pavements. A shift from an empirical to a semi-mechanistic or mechanistic approach is the need of modern time. In this regard, computational tools such as finite element (FE) are being successfully utilized to gain deeper insights because such tools have allowed researchers to study the complex behaviour of bituminous concrete (BC) materials. It is well recognized that BC material typically exhibits viscoelastic/visco-elasto-plastic behaviour depending on applied loading (including temperature) conditions. However, due to the complexity of the whole procedure yet many pavement design tools consider them as pure elastic material. The aim of this research is to develop FEM based simple and practical framework to evaluate the structural response of BC material with viscoelastic material characterization which can be an effective tool to predict field behaviour with commonly available pavement material tests. Such a framework will be helpful in analysing variations in the critical response of BC pavement with varied traffic loads and ambient temperatures. The framework provides a relatively simple procedure to obtain the viscoelastic parameters of BC mix with a creep compliance test conducted at different temperatures. It was concluded that Creep compliance data if pre-smoothened by the Power law model reduces mathematical optimization issues to some extent. Furthermore, with the obtained parameters, a 3-dimensional FE model was developed to obtain sensitivity to critical stresses, strains, and vertical deformations at desired conditions. Material characterization of unbound granular layers was evaluated through resilient modulus based on empirical relations. Analysis was carried out taking into consideration the traffic load, contact pressure, mix type, air-void, and temperature variation.

The relationship between real-world traffic and pavement raveling is unclear and subject to ongoing debates. This research proposes a novel approach that extends beyond traditional correlation analyses to explore causal mechanisms between mixed traffic and raveling. This approach incorporates the causal discovery method, and is applied to five Dutch porous asphalt (PA) highway sites that have substantial data sets. Findings indicate a nonlinear relationship between traffic volume and raveling, with road age emerging as a shared contributor. The results also suggest that the degree to which different vehicle types contribute as a causal factor for raveling varies with carriageway configurations and lane characteristics. This underlines the need for targeted maintenance strategies. Challenges remain due to confounding correlations among traffic variables, necessitating further development of causal discovery models. This study may not conclusively resolve the debate on to what extent traffic contributes to raveling, but we argue we provide sufficient evidence against rejecting this hypothesis.

The ever-growing need to build roads to meet the necessary transportation demands is challenging, especially for developing countries. Low-volume roads (LVRs) are usually the backbone of catalyzing economic growth in these countries. With impediments surrounding Petroleum bitumen (price fluctuations) and environmental concerns, scientists are putting their effort into finding an alternative. The presented research is an attempt to check if Natural asphalt can be used as a full or partial replacement of the Petroleum bitumen. To the best of the authors' knowledge, only limited studies have focused on characterizing and understanding the engineering properties of Natural asphalt. The available techniques do not provide reliable information to the road authorities and hence they are discouraged from using it in practice. Particularly for countries, where the Natural asphalt source is available, the overall dependence on importing the Bitumen could be substantially reduced. Empirical and experience-based design criteria may not be sufficient as the standards were never developed for such materials, hence, a scientific approach is required before bringing it into practice. In this research, Natural asphalt sourced from different locations in Nigeria was assessed. Before performing the mixture level tests using Marshall and Cantabro design methods, the rheological and fatigue properties of the extracted Natural bitumen were examined in the laboratory. In the design of the experiment, various percentages of Natural asphalt were added between 0 % and 20 % by total mix weight; implying that the remaining required fraction of binder was fulfilled by the addition of petroleum bitumen. By using a ranking system (supported by statistics), an optimal design of mixture was obtained which was used in the field (exposed to normal traffic) at 30 different sections.

The linear viscoelastic behavior of materials is represented using mechanical models of choice, which are further utilized in different numerical investigations, such as finite element simulations and discrete element simulations. Burger's model is one of the widely adopted mechanical models and remains highly favored in contemporary research due to its multiple advantages. Specifically, it excels in representing long-term creep and stress relaxation behavior in a relatively simplified manner. Accurate identification of the long-term behavior for the viscoelastic material, particularly asphalt concrete, is crucial, as it serves as a key indicator of asphalt pavement performance over its service life. However, past research studies show that the parameters of Burger's model should be back-calculated from experimental data only within a limited range of frequency, otherwise, the parameters fail to represent the true material behavior. To the best of the authors’ knowledge, there is no approach for researchers to obtain the critical frequency range in which the experiments should be performed. Therefore, this study proposes a novel framework to find the critical frequency range to obtain appropriate model parameters of Burger's model, to better characterize the viscoelastic behavior of the materials. To examine the framework, asphalt concrete mixtures are used as examples in this study. Necessary laboratory tests including complex modulus tests and stress relaxation tests, are performed on two distinctive types of asphalt concrete mixtures. The generalized Maxwell model with different number of Maxwell chains are used to evaluate the performance of Burger's model. Furthermore, since commercially available finite element packages generally do not have a direct built-in Burger's model, the article shows a way of implementing Burger's model in finite element simulation. The simulations corresponding to the laboratory tests are carried out in both frequency domain and time domain to thoroughly evaluate the performance of Burger's model. The optimal frequency range of 0.1–20 Hz for the examined mixtures is found to significantly improve the accuracy of the descriptive master curve. The results also suggest that the generalized Maxwell model requires a minimum of four Maxwell chains to maintain good performance in accurately characterizing the behavior of asphalt mixtures. However, adding more Maxwell chains beyond a critical limit may not provide significant benefits. Finite element simulations demonstrate that the stress relaxation behavior predicted by the obtained Burger's model parameters aligns more closely with experimental data over longer time intervals. This makes Burger's model a strong choice for aiding in the design of simulations for studies focused on the long-term behavior of materials.

The demand for alternative bitumen which could fully/partially replace Petroleum sourced bitumen for pavement construction is globally increasing. The increase in demand can be associated with several factors: depletion in crude oil resources, advances in crude oil refining processes, increased demand for highway infrastructure, and regional transportation-environmental policies. Since the production of Petroleum bitumen consumes energy and generates emissions, there is an effort to decrease harmful emissions which has inspired researchers to look for so-called "green alternatives". Natural bitumen could be considered a green alternative as it is a mixture of bitumen and mineral matter present naturally on earth, mainly if the Natural bitumen can be transported easily to the construction site. This paper reviews the state-of-the-art information on pavement construction using Natural bitumen from laboratory and field perspectives. The Physico-chemical properties, rheological properties and field behaviour of asphalts pavements containing Natural bitumen were assessed. Many road authorities would hesitate to utilise Natural bitumen for pavement applications due to a lack of available data, knowledge and a systematic research study. To the best of the authors’ knowledge, there is no comprehensive literature review article on Natural bitumen. Thus, the presented article aims to comprehensively review Natural bitumen resources and their types, Physico-chemical properties, application in pavement constructions, and reported field performances. At the end of the paper, future research challenges, future recommendations and a methodological framework is proposed.

In the context of climate change and global warming, the attention on the environmental cost of pavements is increasing. To scientifically quantify the environmental cost of pavements, accurate prediction of rolling resistance and fuel consumption is important. In this paper, a comprehensive review on rolling resistance of asphalt pavements and its environmental impact was presented. At first, the commonly used definitions of rolling resistance and texture characterisation methods of pavement surface were introduced. Then, the influence of different factors on rolling resistance was discussed. Next, the measuring and modelling approaches of rolling resistance were reviewed. At last, methods which can be used to predict fuel consumption and environmental impact were presented. It was found that an ideal approach for texture characterisation of pavement surface is to make use of the entire wavelength spectrum of road profiles and consider the enveloping curve of tire treads. Furthermore, the fact that rolling resistance can be influenced by different factors introduces difficulties in accurate measurement and modelling of rolling resistance. Moreover, testing methods and conditions have a significant effect on the empirical modelling of rolling resistance, while it is difficult and time-consuming to consider all the energy loss in the computational modelling of rolling resistance. In addition, the prediction of fuel consumption and environmental impact highly depends on the formulating methods and measuring conditions. The work presented in this paper will help to gain more insight into rolling resistance and its environmental impact, which ultimately promotes the construction of environmentally friendly pavements.

A critical review of lab and field measurement methodologies, harmonization in measuring techniques, and modelling of skid resistance of asphalt concrete pavement have been provided. Although several past studies have provided literature review on general topics of skid resistance, to the best of the author's knowledge, none of them have compressively covered the topic considering the status & requirements of developing nations. There has been significant development in speed with the improvement in computational facilities. In modern times, with the improvement in infrastructure quality in developing nations, permitted speeds have also drastically increased. To avoid skid-related accidents, it is important to develop good practices in maintaining sufficient skid resistance. The requirements and the availability of technology might be significantly different in developing nations. The suitability and limitations of various methods used for capturing the skid characteristics of the surface have been outlined. The harmonization in skid resistance measurement using laboratory and field-testing methods has been summarized. Correlation analysis of various in-situ and laboratory test data has been made to maintain a better harmony of measurement either in the field or in the laboratory. In the subsequent sections, progress in the modelling approach (analytical to numerical) has been discussed in brief. Computational capabilities of an analytical and numerical modelling approach for predicting pavement skid resistance characteristics have been reviewed. These models have been developed to consider complex attributes of tire pavement interactions like hydroplaning, temperature rise in the tire, mix morphology, tire inflation, and vehicle acceleration and deceleration for predicting skid resistance. These attributes of skid resistance have been discussed in detail and presented a basic overview of the model development process which is missing in past review studies. Few recent studies on skid resistance measurement and modelling to highlight the use of new technology and improvements over conventional techniques have been presented in the manuscript which has not been reviewed earlier. Critical factors affecting the skid resistance model like hydroplaning, tire-related parameters, temperature, and surface texture have been highlighted in this manuscript. Few key research directions have been suggested as the scope of future study to predict a more reliable skid resistance model.

The structural evaluation of existing pavements forms the basis for formulating cost-effective maintenance and rehabilitation strategies. A promising tool for pavement structural evaluation at network level is the Traffic Speed Deflectometer (TSD) test. However, the application of the TSD test is hindered by the lack of a robust and efficient parameter identification technique. To solve this problem, a theoretical model for the TSD test is first formulated. Then, a minimisation algorithm which works best with the theoretical TSD model for parameter identification is selected. Finally, the performance of this combination in processing field TSD measurements is studied. The results show that the modified Levenberg-Marquardt algorithm using all the 9 detection points is most suitable to be combined with the theoretical TSD model for parameter identification, which gives a promising parameter identification technique for TSD tests of pavements. The presented work contributes to the development of technologies for pavement structural evaluation.

Membranes of sufficient bonding characteristics could improve the integrity of the multi-layer structures on orthotropic steel deck bridges (OSBDs), enhancing thus the structural response of these systems and, ultimately, their service life. In this research, full-scale experiments were performed at the LINTRACK accelerated pavement testing facility of the Delft University of Technology to evaluate the performance of two surfacing systems commonly used in the Netherlands, giving emphasis on assessing the interface response of membranes with the surrounding materials. Results indicated that the tensile strains remain almost uniform at the top of porous asphalt, in both transverse and longitudinal directions, as no appreciable loss in stress-carrying capabilities was seen even at the end of the testing program. The sections exhibited similar behaviour in terms of strains, with some differences in strains indicating the impacts of membranes at interfaces. The importance of membranes of the desired bonding characteristics was also reflected by the relative displacement measurements. The relative interlayer slip had been higher in the transverse direction than the longitudinal one, with slightly higher displacements in one of the test sections. Overall, no cracking was observed on either section, and the current findings support the use of membranes between surfacing layers on OSBDs.

The existing sources of fresh aggregates are depleting due to the boom in large infrastructure projects. Therefore, this demand necessitates the pursuit of substitute materials and technologies. Foamed bituminous mix (FBM) prepared using reclaimed asphalt pavement (RAP) is one of the alternative solutions that will not only reduce the demand for fresh aggregates but may also minimize the carbon emission during the production of the mix as FBM is a cold mix technique. Therefore, in the present study, an attempt has been made to develop the cold bituminous mix using RAP and foamed bitumen. In this regard, the mix is prepared using fresh and by varying RAP content from 70% to 100%. The influence of RAP on the tensile strength ratio of the foamed bituminous mix is evaluated. Further, resistance against the moisture damage is also determined by assessing the variation in the resilient modulus of the specimen subjected to soaking conditioning. Test results describe that FBM prepared using RAP material exhibits better resilient modulus and less moisture susceptible than the mix prepared using 100% fresh aggregates. Based on the limited laboratory studies it can be concluded that RAP material considerably improves the resistance of the FBM against the moisture damage as compare to fresh aggregates.

First, porous asphalt (PA) pavement possesses a lower strength and lifetime compared to typical dense-grade asphalt mixtures due to its large empty space structure. Second, PA pavements' fatigue life and durability are affected significantly by climate factors; the two most critical factors being aging conditions and moisture actions. Third, because of the environmental concerns connected with producing or repairing asphalt pavements using only virgin materials, studies have recommended reusing reclaimed asphalt pavement (RAP) materials. On the other hand, their use in road pavement is negative to the fatigue performance of asphalt pavements, especially PA. Therefore, modifying PA mixtures containing RAP to address the mentioned issues is necessary. Researchers have found that modifying asphalt mixes using nanotechnology is one of the more effective methods. The four-point bending beam fatigue test is one of the most dependable tests to assess the fatigue performance of asphalt mixtures, and evaluating the fatigue resistance of nano-modified PA mixes containing RAP under laboratory conditions by performing this test is essential. This study aims to investigate the fatigue behavior of different compounds of PA mixtures modified with nano zinc oxide (NZ) (0%, 2%, 4%, 6%, and 8%) containing various contents of RAP materials (0%, 25%, and 50%) under normal, long-term aging, and freeze-thaw (F-T) cycle conditions. Moreover, the self-healing capability of these PA samples was evaluated using this test by performing two 24-h recovery periods following the first and second loading. It can be inferred from the result that although adding RAP and inducting long-term aging and moisture-damaged conditions negatively influenced PA mixes' fatigue lives, incorporating NZ caused increases in these values by averages of 114%. Besides, results indicated that applied rest periods were observed to significantly impact PA specimens' self-healing capability, resulting in longer fatigue life for them. On average, conventional and NZ-modified PA mixes with/without RAP could recover up to 32 and 48% of their fatigue resistance in all conditions.