Pavement Performance Research Articles

Testing and Evaluation of Interlayer Shear Performance of Conductive Rubber Active Deicing Composite Bridge Deck Pavement Structure

Abstract To achieve real-time, sustainable, efficient, and environmentally friendly active deicing of bridge decks, a new active electric heating deicing technology based on conductive rubber as a heat source is proposed in this study. The conductive rubber was laid between asphalt layer and cement layer as the functional deicing layer, and the conductive rubber active deicing composite bridge deck pavement structure was established. The interlayer treatment method of conductive rubber active deicing composite structure was proposed. Styrene butadiene styrene–modified asphalt, PB-II type polymer-modified asphalt waterproof coating, and AMP-100 second-order reactive waterproofing coating were selected as waterproofing bonding layer. The interlayer shear performance of conductive rubber composite structure was tested and evaluated by 45° inclined shear test. Taking shear strength as the evaluation index of interlayer shear performance, the durability of interlayer shear performance of conductive rubber composite bridge deck pavement in complex environment was studied. Taking the fatigue life as the evaluation index, the interlayer fatigue resistance of conductive rubber composite bridge deck and traditional bridge deck under different stress ratios were analyzed. The results showed that shear strength between the layers of the conductive rubber active snow-melting bridge deck pavement structure using PB-II type waterproof bonding layer material was the highest, which was 0.584 MPa, and the optimum dosage was 1.5 kg/m2. Under the complex environment, the interlayer shear performance of conductive rubber composite bridge deck pavement decreases, which could still be maintained at about 70 % and had certain durability. Under the same interlaminar shear stress, the interlaminar shear fatigue life of the conductive rubber active snow-melting bridge deck was reduced by about 34 % compared with the traditional bridge deck. The research results can provide a theoretical basis and data support for the structural design of conductive rubber active deicing bridge deck pavement and the selection of waterproof bonding layer materials.

Geosynthetic stabilization of road pavements, railroads, and airfields

Geosynthetics provide sustainable alternatives for enhanced performance, durability and cost-effectiveness of road pavements, railways, and airfields. Even when the same geosynthetic products are used for constructing these different transportation facilities, an optimal approach is needed to match the properties of soils or unbound aggregate geomaterials and the geosynthetic products to establish an effective mechanical stabilization. This Proctor lecture keynote paper presents the state-of-the-practice on the transportation applications of geosynthetics, design methods, and the recent research findings on geosynthetics used in road and airfield pavements and ballasted railway tracks. The paper introduces first the transportation applications of commonly used geosynthetic products, i.e., geogrids, geotextiles, and geocells, with special emphases to subgrade restraint and unbound aggregate stabilization applications and discusses in detail the related unpaved and paved design procedures. Next, the focus is directed towards establishing a better understanding of geosynthetic mechanisms governing stabilization applications. To summarize, this keynote paper reports on two decades of developments and research findings at the University of Illinois and elsewhere on the topic of geosynthetic stabilization using the latest technologies to quantify the stiffness enhancement in the vicinity of a geosynthetic material via the bearing capacity improvement and lateral restraint mechanisms. Recent research at the University of Illinois focused on the successful use of bender element shear wave transducer technology is discussed in detail with several examples given related to the laboratory and field efforts of unbound aggregate base and railroad ballast geosynthetic stabilization including full-scale instrumentation of stabilization geosynthetics used in actual road and airfield pavements constructed in the United States.

Assessment of flooding impact on thin pavement structure in Texas coastal region

Over the recent years, transportation infrastructure in the United States have experienced numerous hurricanes or tropical storms usually accompanied with heavy rainfalls. This may lead to flooding on pavements and higher groundwater levels, causing soil erosion, slope instability, reduced pavement strength, and lowering pavement’s load-bearing capacity, subsequently shortening pavement service life or increasing rehabilitation and maintenance costs. This study focuses on the impact of flooding on thin pavement structure with surface-treated pavements in Texas coastal region, which contains 6,277 lane miles of roads. First, at a project level, a Mechanistic-Empirical pavement design tool is used to analyze pavement performance under flooding and non-flooding/normal conditions. Pavement life is estimated for different flooding timing cases. Second, simulations are run to evaluate the impact of flooding on the pavement life at a network level. Three flooding frequencies are highlighted: low, 100-year; medium, 50-year; and high, 20-year. By a comparison with non-flooding baseline, it is found that the pavement life for the entire weak pavement network in the coastal region can be reduced at varying degrees due to the flooding impact. The quantified pavement life reduction can serve to enhance pavement design practice and system management decision making in a proactive manner.

Assessment of Ground Tyre Rubber Impact on Stiffness Modulus and Cracking Resistance of Bituminous Mixtures

Abstract The objective of this study was to evaluate and characterize the performance of ground tire rubber (GTR) modified dense graded asphalt mixtures to recommend a suitable GTR content to produce a mix that provides superior pavement performance characteristics. The research effort encompassed investigation of stiffness and cracking resistance of six dense graded asphalt mixtures, including one conventional and five modified mixes covering 42 samples. Addition of GTR using wet process showed decrease in stiffness during loading. Cracking resistance of GTR modified mixtures increased with higher levels of dosages regardless of the base binder. An increase in the GTR dosage from 0 to 10% did not result in a significant change in fracture energy but a further increment to 25% increased the fracture energy. The laboratory Results indicated that 10% GTR was showed as the optimal content for the stiffness modulus and 25 % GTR as better content that provides better cracking resistance.

Pavement Performance of Fine-Grained Soil Stabilized by Fly Ash and Granulated Blast Furnace Slag-Based Geopolymer as Road Base Course Material

Pavement Performance of Fine-Grained Soil Stabilized by Fly Ash and Granulated Blast Furnace Slag-Based Geopolymer as Road Base Course Material

Enhancing Roads Infrastructure Monitoring with FBG Sensors and Multi-Threshold Signal Tracking

Accurate monitoring techniques are needed to improve pavement durability by ensuring their structural integrity and longevity. This study developed an innovative real-time monitoring system utilizing fiber Bragg grating (FBG) sensors embedded in asphalt layers. The data collected by FBG sensors includes a baseline primarily influenced by temperature and peak shape data associated with short-term loading from passing vehicles. Therefore, analyzing FBG data and identifying statistical patterns poses a challenge. To address this challenge, employing a signal tracker proves to be a valuable option for monitoring the baseline and scanning signals for subsequent analysis. Moreover, considering the varying loading weights on FBG sensors due to diverse vehicles, tracking FBG signals across multiple thresholds enhances precision. A MATLAB-based program was developed incorporating a multi-threshold signal tracker capable of efficiently processing FBG data by tracking signals in both positive and negative multi-thresholds. This tracker effectively distinguishes between different loading events and extracts the baseline signal after tracking. Subsequently, the system provides outputs, including loading distribution, number of loading events, traffic, and temperature effects. Finally, to validate the system, real FBG data collected during an extensive monitoring campaign was processed using the developed program. The obtained outputs contribute to a comprehensive assessment of pavement performance, thereby facilitating the development of more accurate maintenance and rehabilitation strategies.

Integrating Machine Learning for Improved Prediction of Temperature and Moisture in Pavement Granular Layers

Abstract Pavement temperature and moisture content within the base and subgrade layers affect the load-bearing capacity of the pavement and dominate the pavement performance in cold regions. Accurately predicting pavement temperature and moisture content can improve pavement design and management. Conventional approaches, including numerical and statistical models, have been implemented to predict pavement temperature and soil moisture content. However, they have weaknesses, such as being only suitable for warm regions or only for predicting pavement temperature within the asphalt layer. Furthermore, none of them can simultaneously predict the pavement temperature and moisture content. To address this issue, data collected from an instrumented test road in Alberta, Canada, were used to train a model to predict the daily average pavement temperature and moisture content at various depths through three parameters, namely depth, day of the year, and air temperature. The MATLAB toolbox, Neural Net Fitting, was used, and the performance of three built-in algorithms, Levenberg–Marquardt, Bayesian regularization, and Scaled conjugate gradient backpropagation, was compared. The model with Bayesian regularization showed the highest accuracy, with an R2 value of 0.99 and a root mean square error (RMSE) of 1.49°C for pavement temperature prediction, and an R2 value of 0.95 and an RMSE of 0.025 m3/m3 for moisture content prediction. The model developed in this research is the first to simultaneously estimate pavement temperature and moisture content, so its performance was separately compared with two existing models in the literature. The artificial neural network (ANN) model shows higher accuracy than the two existing models, so it was found that the ANN could be a robust method for pavement temperature and moisture content prediction at various depths.

Laboratory investigations on influence of thermoplastic polyurethane and its hard segment content on pavement performance of asphalt mixture

ABSTRACT Thermoplastic polyurethane (TPU) is an excellent asphalt modifier, which is consisted of hard and soft segments in the TPU molecular chain. In this paper, The conventional road performances (high and low temperature performance, water stability, fatigue performance and aging resistance) of TPU modified asphalt mixture (TPU-AM) with different hard segment content were evaluated. The results proved that the hard segment of TPU can effectively improve the high temperature performance of asphalt. Compared with TPU-AM with high hard segment content, using TPU with low hard segment content as modifier, the low temperature flexibility and fatigue resistance of TPU-AM are significantly improved. TPU-AM with hard segment content of 40% has excellent high temperature performance, while the TPU-AM with hard segment content of 10% has the best fatigue ability and low temperature performance. The water stability of TPU-AM is obviously stronger than that of base asphalt mixture, although the content of TPU hard segment has little influence on the water stability of TPU-AM. The aging results show that TPU-AM has the best aging resistance when the hard segment content is 30%. Based on the above analysis, the high performance of TPU-AM can be designed by changing the hard segment content.

Hubungan Antara Rasio Agregat dan Volumetrik dalam Menentukan Kualitas Perkerasan Jalan

Road pavement quality is a critical factor in supporting a country's mobility and economy. Around 40% of the road length in Indonesia suffers damage, including permanent deformation and early cracking. To overcome road damage, it is important to know the pavement quality parameters such as Voids in Mineral Aggregate (VMA), Voids in Mix (VIM), and Voids Filled with Bitumen (VFB), along with the factors that influence them, such as material characteristics. This study aims to determine the effect of the fine and coarse aggregate ratio on volumetric parameters in asphalt mixtures, including VIM, VMA, and VFB. The experimental method was carried out on four samples. Aggregate characteristic tests were carried out, including gradation tests. Volumetric tests were carried out on each sample with asphalt content of 4%, 4.5%, and 5%. The research results show that the smaller fine-to-coarse aggregate ratio would increase the VMA and VIM values and decrease the VFB value. Aggregate ratio significantly affects volumetric parameters, which shows the importance of selecting aggregate with the right size distribution and determining the right ratio to achieve optimal pavement performance. The results of this study can be used as a practical guide for optimizing asphalt mix design with better quality and durability.

Effect of glass waste powder and date palm seed ash based sustainable cementitious grouts on the performance of semi-flexible pavement

Cement plays a pivotal role in the production of semi-flexible pavement (SFP), however, it contributes to 8 % of global carbon dioxide emissions. Consequently, reducing cement usage in grout production for porous asphalt mixtures is highly desirable to mitigate the overall carbon footprint. Additionally, the substantial generation of agricultural, industrial, and hazardous waste often ends up in environmental disposal without recycling. This research aims to repurpose glass waste powder (GWP) and date palm seed ash (DPSA) as partial substitutes for cement in SFP, aiming to curtail environmental pollution from cement production, decrease costs, and enhance waste and landfill management. Novel cement grouts were formulated by partially replacing Portland cement with GWP and DPSA at varying ratios (10 %, 20 %, and 30 %). These grout blends were assessed for flow characteristics and compressive strength. Furthermore, SFP samples were prepared by integrating 5 % styrene-butadiene-styrene (SBS)-modified bitumen into a porous asphalt structure, subsequently filled with predefined cement grouts. Comparative analysis of compressive strength, Marshall stability, skid resistance, and moisture damage resistance indicated that SFP specimens modified with GWP and DPSA exhibited superior performance over conventional counterparts. Optimal results were achieved with a combination of 20 % GWP and 10 % DPSA replacement ratio, yielding denser microstructure, enhanced skid resistance, and improved adhesion and tensile strength, thereby enhancing overall SFP performance.

Impact of aggregate gradation and asphalt-aggregate ratio on pavement performance during construction using back propagation neural network

This paper evaluates the influences of variations in asphalt mixture parameters during construction on the variations of pavement performance using back-propagation (BP) neural networks. The variations of gradation (VG) and asphalt-aggregate ratio (VRa) were assessed through a variability analysis. The influences of VG and VRa propagation were analyzed via BP neural networks and a sensitivity analysis. A reliability assessment was conducted to evaluate the joint effects of VG and VRa. Results illustrate that the VG and VRa during transportation are more severe than those during other processes. BP neural networks can precisely and robustly trace the influences of the VG and VRa. Pavement performance exhibits greater sensitivity to VRa and VG at sieve sizes of 0.075 mm and 2.36 mm. The joint effects of VG and VRa significantly degrade permanent deformation more than fatigue life. High-quality paving effectively mitigates the negative impacts of segregation during transportation.

An investigation toward adhesion characteristics of emulsified asphalt residue–aggregate interface through MD simulation

The bonding ability of emulsified asphalt residue-aggregate interface is crucial for improving the pavement performance of emulsified asphalt mixtures. The aim of the study was to explore the adhesion mechanism and characteristics of emulsified asphalt residue-aggregate interface under the different emulsifier contents using molecular dynamics (MD) simulation. Firstly, the emulsified asphalt residue-aggregate interface model was established, and its validity was validated through the related thermodynamic properties. Secondly, the performance-related parameters were employed to discuss the molecular arrangement features of emulsified asphalt residue components on the aggregate surface, and investigate the interfacial adhesion mechanism. Thirdly, the adhesion strength of emulsified asphalt residue-aggregate interface was calculated and evaluated by the adhesion energy. Lastly, the influence of temperature and moisture on the interfacial adhesion strength was further examined through the molecular orientation theory and the electrostatic interaction theory. The results indicate that the addition of emulsifiers could affect the aggregation behaviors and distribution characteristics of asphalt components as observed from performance-related parameters. When compared to relatively high emulsifier content (4–6 %), the molecular arrangement of emulsified asphalt residue components with relatively low emulsifier content (1–3 %) is more similar to that of the base asphalt and exhibits greater interfacial adhesion strength with aggregates. The polar components and emulsifiers in emulsified asphalt residue with relatively low emulsifier content are minor affected by the increase of temperature, which further proving that interfacial adhesion strength is higher at this condition. Meanwhile, emulsified asphalt residue with relatively low emulsifier content is confirmed to have better moisture damage resistance due to the existence of the certain number of Silica-Water(S-W) and Asphalt-Water(A-W) hydrogen bonds near interface. Moisture exhibits more significant influence on the interfacial adhesion strength between emulsified asphalt residue and aggregates according to the results of the average adhesion energy. It is advisable to apply emulsified asphalt with moderate emulsifier content during the actual production process considering the influence of moisture and temperature on the pavement performance of emulsified asphalt mixtures.

Exploring the effects of volumetrics and binder properties on the performance of asphalt mixtures

Current design methods rely mainly on the volumetric properties of asphalt mixtures. More comprehensive mixture analyses facilitate a broader understanding of the pavement performance as a function of factors such as traffic, climate, and mixture properties. Recently, performance-based mix designs have been developed to overcome shortcomings of the volumetric-based designs. Nevertheless, these new approaches may be time-consuming and expensive, and establishing a comprehensive understanding of the interplay between binder characteristics, volumetric properties, and performance outcomes becomes crucial. This work aims to explore relationships among these three aspects of asphalt mixtures regarding fatigue cracking and rutting performance. A database from different Brazilian studies and tests were collected. Data exploration analysis was conducted to evaluate the effect of the binder and volumetric properties on the fatigue and rutting results. The statistical analyses conducted in this study highlight that most properties within the database significantly impact asphalt mixture performance. Additionally, clear relationships were identified between various performance parameters. Lastly, multivariate analyses pinpointed key volumetric and binder variables that predominantly influence the mixture performance, particularly in relation to fatigue and rutting results.

Geopolymer Cement in Pavement Applications: Bridging Sustainability and Performance

Sustainability and the quest for a more robust construction material cannot be divorced from each other. While Portland cement has revolutionized the construction sector, its environmental toll, particularly in greenhouse gas emissions and global warming, cannot be ignored. Addressing this dilemma requires embracing alternatives like geopolymer cement/geopolymer binder (GPC/GPB). Over the last few decades, considerable strides have been achieved in advancing GPC as a sustainable construction material, including its utilization in pavement construction. Despite these advances, gaps still exist in GPC optimal potential in pavement construction, as most studies have concentrated on specific attributes rather than on a comprehensive evaluation. To bridge this gap, this review adopts a novel, holistic approach by integrating environmental impacts with performance metrics. To set the stage, this review first delves into the geopolymer concept from a chemistry perspective, providing an essential broad overview for exploring GPC’s innovations and implications in pavement applications. The findings reveal that GPC not only significantly reduces greenhouse gas emissions and energy consumption compared to Portland cement but also enhances pavement performance. Further, GPC concrete pavement exhibits superior mechanical, durability, and thermal properties to ensure its long-term performance in pavement applications. However, challenges to GPC utilization as a pavement material include the variability of raw materials, the need for suitable hardeners, the lack of standardized codes and procedures, cost competitiveness, and limited field data. Despite these challenges, the process of geopolymerization presents GPC as a sustainable material for pavement construction, aligning with Sustainable Development Goals (SDGs) 3, 9, 11, and 12.

Effects of Thermo-Chromic materials (TCMs) on the performance of asphalt pavement with phase change materials (PCMs)

Temperature regulation is crucial for the longevity of pavements. Thermo-Chromic Materials (TCMs) is proposed for effective temperature regression in pavements with Phase Change Materials (PCMs). In this paper, the performance of asphalt pavements in a typical year is investigated with Abaqus, including the peak temperature, the variation of surface temperature and the properties of PCMs before and after the adoption of TCMs. The incorporation of PCMs resulted in a reduction of peak pavement temperatures by 1.3 °C, while the addition of TCMs further decreased temperatures by 38.5 °C. By comparison with the results with and without PCMs as well as with and without TCMs, it is concluded that both PCMs and TCMs may reduce the peak temperature of asphalt pavements. However, TCMs may further regress the peak temperature but does not result in the time delay of peak temperature, as PCMs does. The peak temperature positively correlates with the variation of surface temperature. Nevertheless, although only four types of correlation between the temperature property of TCMs and that of PCMs are involved, the profile or status of PCMs is much more complicatedly influenced after the adoption of TCMs, indicating the interaction between TCMs and PCMs. More time of PCMs is in the phase of solid, due to the modulation of solar radiation. As far as the peak temperature is considered, it is also possible to reduce the amount of PCMs applied in pavements, with the adoption of TCMs. According to the results in this paper, the application of TCMs in an asphalt pavement with PCMs may be an effective way to reduce the peak temperature, to regress the daily variation degree as well as to improve the performance of PCMs.

Evaluation of Fatigue Behavior of Asphalt Field Cores Using Discrete Element Modeling.

Fatigue cracking is one of the primary distresses of asphalt pavements, which significantly affects the asphalt pavement performance. The fatigue behavior of the asphalt mixture observed in the laboratory test can vary depending on the type of fatigue test and the dimension and shape of the test specimen. The variations can make it difficult to accurately evaluate the fatigue properties of the field asphalt concrete. Accordingly, this study proposed a reliable method to evaluate the fatigue behavior of the asphalt field cores based on discrete element modeling (DEM). The mesoscopic geometric model was built using discrete element software PFC (Particle Flow Code) and CT scan images of the asphalt field cores. The virtual fatigue test was simulated in accordance with the semi-circular bending (SCB) test. The mesoscopic parameters of the contacting model in the virtual test were determined through the uniaxial compression dynamic modulus test and SCB test. Based on the virtual SCB test, the displacement, contact forces, and crack growth were analyzed. The test results show that the fatigue life simulated in the virtual test was consistent with that of the SCB fatigue test. The fatigue cracks in the asphalt mixture were observed in three stages, i.e., crack initiation, crack propagation, and failure. It was found that the crack propagation stage consumes a significant portion of the fatigue life since the tensile contact forces mainly increase in this stage.

Development and characterization of anti-cracking epoxy asphalt for steel deck pavement

Despite being commonly utilized in long-span steel deck pavement, epoxy asphalt continues to encounter certain obstacles, including excessive strength and insufficient resistance to cracking. This study proposed a novel approach to incorporating epoxy-terminated polyurethane prepolymers (ETPU) as a toughener to prepare an anti-cracking epoxy asphalt binder. The reaction process, viscosity-time behavior, tensile properties, and dynamic mechanical features of the ETPU-modified epoxy asphalt binder were comprehensively evaluated through a series of tests. Additionally, the fundamental pavement performance, fracture resistance, and fatigue resistance of ETPU-modified epoxy asphalt mixtures were thoroughly assessed. The addition of ETPU can significantly enhance the damping properties of epoxy asphalt, while maintaining its strength and construction retention time without any significant compromise. The formation of a chemical bond between epoxy-amine molecules and asphalt molecules significantly enhanced the compatibility between the epoxy resin phase and asphalt, thereby improving its damping properties. Both the fracture resistane and the fatigue resistance of ETPU-modified epoxy asphalt mixtures were found to be superior to that of commonly used epoxy asphalt mixtures in engineering. The modification mechanism was ultimately derived through the integration of infrared spectral analysis, thereby presenting an economically viable and highly efficient toughening pathway for epoxy asphalt. Therefore, this study indicated a wide-ranging potential for application in the realm of steel bridge deck pavement.

Assessment of Relationship between Asphalt Concrete Pavement Performance Indicators: Pavement Condition Index and RoadRoid based International Roughness Index

Pavement condition assessment is one of the important tasks to be carried out to prioritize maintenance needs of the road. The Pavement Condition Index and International Roughness Index are some of the most widely used and comprehensive indices for the assessment of pavement condition. The maintenance planning is generally carried out in terms of SDI in Nepal which is only a subjective measure so PCI can be used as a more objective indicator than SDI. The PCI is more representative of the overall condition of the pavement surface by considering all forms of distresses. Whereas, IRI, which is a measure of perceived road roughness is mainly concerned with the ride quality and is based on the distresses occurring on the wheel path. The research aimed to develop the correlation between the two indices to look for usability of either of the indices whenever required. For the determination of PCI, visual inspection survey was carried out based on which the distress type, density and severity were quantified. The IRI data was collected with the help of RoadRoid application after calibration and validation using Laser Profiler. The data matching in respective sections was carried out and relationships between the two indices are determined in terms of linear, logarithmic and polynomial models of different degree. The coefficient of determination for polynomial relationship model was found to be the highest with coefficient of determination of 0.7858. All the models presented with negative correlation between the indices indicating the increase in IRI would cause the decrease in PCI value and vice versa.

Real-time pavement temperature prediction through ensemble machine learning

Pavement temperature is crucial for assessing asphalt pavement's performance and structural integrity due to its viscoelastic behavior. Currently, asphalt temperature prediction includes analytical, numerical, and statistical methods and relies on field investigation with intensive labor and time to hinder routine practice. Machine learning (ML) offers a promising solution for reliable and accurate real-time predictions by considering various dynamic environmental factors. This research employs four ensemble ML algorithms: eXtreme Gradient Boosting (XGB), Light Gradient Boosting Machine (LGBM), Random Forest (RF), and Adaptive Boosting (AdaBoost) to predict pavement temperature at different depths. XGB consistently outperformed other ensemble models, boasting the highest average R2 value (97.92%) and lower MAE and RMSE than LGBM, RF, and AdaBoost. XGB also significantly outperformed other commonly used models (linear regression, SVR, ANN, LSTM, and GRU) with an average reduction in errors of 35.29%, 63.75%, 42.75%, and an increase in R2 by 4.39% for MAE, MSE, RMSE, and R2, respectively. The Shapley additive explanation (SHAP) was applied to interpret the underlying influencing factors and their interactions, and revealed atmospheric temperature as the most impactful feature, contributing over 40.58% among the significant features.Furthermore, the predictive performance of XGB was enhanced by incorporating Principal Component Analysis to reduce computational consumption with average reductions of 8.98%, 16.59%, 9.01%, and 7.89% in MAE, MSE, MAPE, and RMSE. XGB with PCA emerges as the most effective and efficient model for predicting pavement temperatures at various depths to facilitate timely decision-making for preventive maintenance and rehabilitation and prevent future catastrophic failures.

Optimising Pavement Performance in Douala City Using a Mixture of Clay and Sand Fractions

Pavements are complex structures composed of multiple layers, designed to withstand various types of stress, including mechanical, organic, and climatic. The pavement is constantly subjected to cyclic, dynamic-mechanical actions caused by road traffic and different axle loads. Classified as engineering structures, the standard theoretical durability of this type of construction is generally estimated to be around one hundred years. However, this objective may not be achieved if the designer does not take into account certain specific factors that are endogenous and exogenous to the structure. Therefore, the durability of a road can be achieved through an optimized design that meets the needs defined by the public authorities and the context of its socio-economic framework. This passage discusses the factors that affect the performance of pavements, including soil type, machinery used, users, and climatic conditions. Exceeding axle loads, which form the basis of pavement design calculations, is also a disruptive factor from a civic perspective. A pavement consists of multiple layers, each made up of materials that must meet strict quality criteria and respect the anthropological, economic, social, and natural environment. It is important to consider all of these factors when constructing a pavement to ensure its longevity and avoid any negative impacts on the surrounding area. Additionally, it is crucial to maintain the pavement to prevent any loss of economic or infrastructural development opportunities. Several road infrastructures in urban and inter-urban areas experience issues that result from a combination of causes, each with varying degrees of impact. Douala is one such city where civil engineering projects are subject to an environment that is not conducive to the longevity of infrastructure, especially road infrastructure. The city is situated on a surface layer covered by a predominantly sandy-clay soil. This study aims to propose a proportional mixture of clay and sand soil fractions to create an anvil effect during compaction. The objective is to create a hybrid backfill material that can achieve a high compaction rate. Good compaction is crucial for achieving optimal pavement layer performance. The thickness of the material to be laid is greatly affected by this characteristic, which in turn affects the volume of equipment depreciation and user comfort. This has a significant impact on a wide range of socio-economic benefits. Based on soil mechanics and geotechnical tests, a new material is proposed to combat the early onset of disorders such as potholes, ruts, erosion, or pavement collapse in bad weather or heavy traffic.