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Intelligent compaction (IC) has emerged as a breakthrough technology that utilizes advanced sensing, data transmission, and control systems to optimize asphalt pavement compaction quality and efficiency. However, accurate assessment of compaction status remains challenging under real construction conditions. This paper reviewed recent progress and applications of smart sensors and machine learning (ML) to address existing limitations in IC. The principles and components of various advanced sensors deployed in IC systems were introduced, including SmartRock, fiber Bragg grating, and integrated circuit piezoelectric acceleration sensors. Case studies on utilizing these sensors for particle behavior monitoring, strain measurement, and impact data collection were reviewed. Meanwhile, common ML algorithms including regression, classification, clustering, and artificial neural networks were discussed. Practical examples of applying ML to estimate mechanical properties, evaluate overall compaction quality, and predict soil firmness through supervised and unsupervised models were examined. Results indicated smart sensors have enhanced compaction monitoring capabilities but require robustness improvements. ML provides a data-driven approach to complement traditional empirical methods but necessitates extensive field validation. Potential integration with digital construction technologies such as building information modeling and augmented reality was also explored. In conclusion, leveraging emerging sensing and artificial intelligence presents opportunities to optimize the IC process and address key challenges. However, cooperation across disciplines will be vital to test and refine technologies under real-world conditions. This study serves to advance understanding and highlight priority areas for future research toward the realization of IC's full potential. [ABSTRACT FROM AUTHOR]

In order to build an appropriate prediction model of pavement friction coefficient attenuation, the effects of aggregate texture, on a basis of texture scanning and pavement testing of the dynamic friction coefficient, traffic volume, and rock characteristics on pavement slide decay resistance were studied, and the accuracy of the developed prediction model of friction coefficient was thereafter compared and analysed. First, based on the tire-pavement dynamic friction analyzer independently developed by the research group, accelerated loading tests under different traffic conditions were conducted by the orthogonal test method, and the dynamic friction coefficient of pavement during the abrasion process was recorded. At the same time, the non-contact laser profile measurement system was used to collect three-dimensional micro-texture data of coarse aggregate surface at different abrasion stages, and characteristic parameters such as height, wavelength, and shape were calculated. Second, the factors such as traffic volume and rock characteristics were incorporated, and the algorithms such as multiple linear stepwise regression, feedforward neural network, and random forest regression were adopted to develop estimation models of pavement friction. The results showed that the model constructed based on only texture feature parameters poorly represented pavement skid resistance. After introducing the two indicators of total traffic volume and rock type, the correlation coefficients of the model significantly improved, reaching 0.63, 0.58, and 0.82 respectively, indicating that the latter two factors have significant effects on the anti-skid attenuation of pavement. Moreover, the above three models can achieve satisfactory prediction results. In addition, when a large sample size can be obtained, a random forest algorithm is recommended to acquire higher prediction accuracy of pavement friction coefficient attenuation. [ABSTRACT FROM AUTHOR]

The evaluation of in-service pavements' performance is a complex system that encompasses a variety of uncertain factors. These uncertainties include random, fuzzy, gray, and unascertained information, and their interrelationships are intricate, making comprehensive quantification unachievable. Nonetheless, current highway management organizations rely on a comprehensive indicator, namely, the Pavement Quality Index (PQI), to assess the level of pavement performance. This paper introduces a novel approach that employs blind number theory to evaluate the reliability of pavement performance test data. The proposed method aims to enhance the representativeness of PQI and is demonstrated using detection data from highway asphalt pavements in Hunan Province. The method takes into account the probability distribution characteristics of evaluation metrics and incorporates the blind number representation format of PQI. A confidence model for pavement performance evaluation is established to assess the reliability of pavement detection results. The method also integrates expert empowerment and entropy weight to consider both the subjectivity of evaluation and the objectivity of measured data. The method presented in this study has demonstrated superior performance compared to traditional evaluation index systems. This is attributed to the effective utilization of blind information to accurately characterize the discreteness of pavement performance indexes. Consequently, pavement performance can be quantitatively graded based on anticipated issues and data. [ABSTRACT FROM AUTHOR]

In the laboratory, there are significant differences in mechanical properties of asphalt mixtures with the same size gradation and asphalt binder, which is not conducive to evaluating and designing the pavement structure accurately. Meanwhile, the influence of aggregate segregation in height on the mechanical properties of asphalt mixtures is unclear. This study developed a new method to generate a three-dimensional (3D) model of the real composition and aggregate shape to characterize the aggregate segregation during Superpave gyratory compaction (SGC). The graphic segregation index (GPSI) is employed to assess the mixing degree of coarse aggregate and asphalt mortar within spatially variable specimens [i.e., Superpave-13, stone mastic asphalt (SMA-13), and open-graded asphalt friction course (OGFC-13) mixtures]. The results reveal that asphalt mixtures with different aggregate gradations have different compaction characteristics. For example, the increase of fine aggregates may reduce the strain energy and the average contact force during compaction. The compaction curves of the three gradation types were very different, which is attributed to different packing states and gyratory numbers. Aggregate segregation has a significant effect on micromechanical behavior. Specifically, the contact number and the proportion of strong contact force change considerably with height. In terms of segregation degree, the GPSI of OGFC-13 specimens was the highest, and the volume change of its fine particles created a leakage zone after the compaction. Additionally, this segregation had an increasing tendency with gyration numbers, and it was influenced by gradation types. Furthermore, the uniaxial compressive strength and cohesion of the Superpave-13 specimen decreased, whereas the friction angle increased with the increase of GPSI. [ABSTRACT FROM AUTHOR]

Granular base material (GBM) is widely used as the base/subbase course of pavement structure. In the mechanic–empirical design of flexible pavement, both the resilient modulus and permanent deformation are the major deformation properties of base materials, related to early-stage distresses of the surface layer under traffic loading. However, since the microscopic interaction between aggregates of the GBM is quite complex, the deformation behavior was not to be understood merely empirically. This study aims to evaluate the macroscopic and microscopic behavior of the GBM under repeated load triaxial (RLT) testing by the discrete-element method. Both the size gradation and the aggregate shape were considered in numerical simulations. The modeling technology of a heterogeneous structure was developed and verified by laboratory results. The results showed that the resilient modulus measured by the developed simulation was in good agreement with that of laboratory tests, within errors of 5.0%. The deformation behavior of the GBM presents the stress-hardening characteristic that the resilient modulus of the GBM increases from 94.03 to 337.71 MPa with the growth of the volume stress and deviator stress. The microstructure of the GBM maintain a relatively stabilization in dynamic response and anisotropy changes during the cyclic loading and voids within aggregates play a role in buffering the change in internal stress. The principal contact normal trends to the direction of maximum bulk stress through small motions, and rotations of aggregates during the loading. It provides a robust mechanism for the resistance to deformation, which results in dispersing more stresses into the skeleton. [ABSTRACT FROM AUTHOR]

The sustainable performance of asphalt pavement depends on the quality and mix design of road aggregates. Identifying aggregate morphology and size is a prerequisite step for material design and numerical modeling of asphalt mixtures. The paper aims to review the morphometric measurement, characteristic parameters and visualization technique of road aggregates. Types, calculation methods and advantages of aggregate morphological characteristics are highlighted. The applications of aggregate morphological features on the volumetric design, compaction processes, mechanical properties and size effect of asphalt mixtures are summarized. Although digital image processing technology has been studied for years, aggregates in the complex accumulation are still difficult to measure accurately. In the current research, the morphological parameters of aggregates remain diverse without a standard protocol. Compared to theoretical models, numerical models have more difficulties establishing irregular morphology features in the simulated specimens but provide a volume parameter closer to the real value. The future investigation of road performance under dynamic loading should account for the microscopic evolution of shape, orientation and distribution of aggregates over time. [ABSTRACT FROM AUTHOR]

This study presented a finite element model of radial tire–asphalt pavement interaction using ABAQUS 6.14 software to investigate the skid resistance properties of asphalt pavement under partial tire aquaplane conditions. Firstly, the pavement profile datum acquired by laser scanning were imported to Finite Element Analysis (FEA) software to conduct the pavement modeling. Secondly, a steady state rolling analysis of a tire on three types of asphalt pavements under drying conditions was carried out. Variation laws of the friction coefficient of the radial tire on different pavements with different pavement textures, tire pressures, and loads on the tire were examined. Subsequently, calculation results of the steady state rolling analysis were transmitted to dynamic explicit analysis, and an aquaplane model of a radial tire on asphalt pavements was built by inputting the flow Euler grids. The tire–pavement adhesive characteristics under partial aquaplane conditions are discussed regarding the aquaplane model. Influences of the thickness of water film, the texture of asphalt pavement, and the rolling speed of the tire on the vertical pavement-tire contact force are analyzed. It is found that the vertical contact force between open graded friction course (OGFC) pavement and tire is the highest, followed by stone mastic asphalt (SMA) pavement and dense graded asphalt concrete (AC) pavement surface. The vertical contact force between tire and pavement will be greatly reduced, even with increasing speed or water film thickness. As tire speed increases from 70 km/h to 130 km/h, the tire–pavement contact force is reduced by about 25%. Moreover, when the thickness of water film increases from 0 (dry condition) to 4 mm and then to 12 mm, the vertical contact force reduced 50% and 15%, respectively, compared with under the dry contact condition. This study provided a key theoretical reference for safe driving on wet pavements. [ABSTRACT FROM AUTHOR]

In view of the deficiency that traditional pavement performance evaluation index did not consider the influence of their difference on weight, the grade of the evaluation index also did not take into account intermediate state and the impact of uncertainty on the evaluation results, a determination method of pavement performance evaluation index weight based on entropy theory was developed. The unascertained measurement function of evaluation index was performed by left-half ladder distribution, and unascertained measurement matrix was obtained. The index weight was calculated by minimum entropy theory, and the practicability of this method was verified through a concrete example finally. The results show that there were different weights in different samples, which depended on index measurement function and were the overall characterization of comprehensive measurement of every index. The method which is based on the given weighting factor did not conform to the engineering facts. It was difficult to identify the importance of the pavement performance evaluation index in different samples. The balance of the various indexes is better to be considered in the proposed method, and the comprehensive situation of pavement performance is really reflected, which improves the evaluation of the reliability. [ABSTRACT FROM AUTHOR]

• Emissions of volatile organic compounds (VOCs) in asphalt are investigated. • Factors influencing the emissions of VOCs in modified asphalt are analyzed. • A correlation between the release of VOCs and asphalt performance is built. With the booming construction of asphalt pavements, the volatile organic compounds (VOCs) emission becomes a growing threat to the environment and people's health. This paper aimed to investigate the impact of Buton rock asphalt (BRA) on VOCs emissions and the high-temperature rheological properties of modified asphalt. The investigation encompassed four different levels of BRA content, heating temperatures, and exposure durations, which were subjected to range analysis to ascertain the emission characteristics of BRA modified asphalt in terms of VOCs. Furthermore, the high-temperature rheological properties were assessed through dynamic shear rheometer (DSR) tests, and the correlation between asphalt VOCs characteristics and performance indicators was analyzed. The results showed that the emissions of VOCs increase significantly with rising temperatures and longer exposure to light. However, the incorporation of a 50% BRA modifier effectively reduced VOCs emissions by 8.84% while improving the high-temperature properties of asphalt. Additionally, a positive correlation was observed between the emission behavior of asphalt VOCs and the rheological properties of BRA modified asphalt. Overall, this study provides valuable insights into the environmental effect of BRA modified asphalt and it's potential as a sustainable alternative to traditional asphalt materials. [ABSTRACT FROM AUTHOR]

Coarse aggregate is the major part of asphalt mixture, and plays an essential role in mechanical performance of pavement structure. However, the use of poor-quality coarse recycled aggregate (CRA) reduces the strength and stability of the aggregate skeleton. It is a challenge to predict accurately the influence of CRA on the performance of asphalt mixture. In this study, both a uniaxial compression test and a direct tensile test were carried out to evaluate the failure strength of asphalt concrete with four CRA content. The discrete element method (DEM) was applied to simulate the specimen of asphalt concrete considering the distribution and properties of CRA. The results showed that temperature and loading rate have a significant influence on failure strength, especially when the CRA content was more than 20%. With the increase of CRA content, both cohesion force and internal friction angle were gradually weakened. The proposed model can be used to predict the failure strength of asphalt mixture, since both experimental and simulated results had a high consistency and repeatability. With the decrease of CRA strength, the nominal cohesion force of the specimen decreased, while the internal friction angle increased. [ABSTRACT FROM AUTHOR]

This paper presents a microcrack segmentation method and two-dimensional planar parameters to quantitatively characterize microcracks in aggregates under tire loading. First, an aggregate sample with extensive repeated tire wear was collected from the pavement surface for rock CT scanning. The acquired grayscale images were pre-processed by image filtering and appropriate image enhancement. Then, a microcrack segmentation method for aggregate damage analysis was developed based on the edge region growth algorithm and compared with the traditional threshold segmentation method. Finally, based on the microcrack segmentation results, the distribution pattern of microscopic characteristic parameters of aggregate surface microcracks was revealed. The results show that the best image pre-processing scheme is to first reduce the noise in the gray-scale images by using the Gaussian and median filters together, and then enhance their local details by gamma transform. Compared with the traditional threshold segmentation method, the proposed method effectively improves the microcrack segmentation accuracy by setting a large number of seed positions and adjusting their growth patterns. Moreover, the microscopic characteristic parameter distribution pattern of aggregate microcracks in each layer suggests that the crack extension degree on the pavement aggregate surface directly subjected to tire loads is generally larger than that on other parts. In addition, the microcracks are not only densely distributed within the aggregate surface layer, but also tend to extend deeper, indicating that the effect of cumulative tire loads on frictional damage to the pavement surface needs to be investigated in the field of pavement skid resistance research. • A new perspective for the analysis of aggregate wear is proposed. • The distribution location of aggregate microcracks under the cumulative effect of tire load is investigated. • The segmentation method and corresponding evaluation parameters of aggregate microcracks are proposed based on CT scanning. • The propagation trend of microcracks on the aggregate surface under the cumulative effect of tire load is discussed. [ABSTRACT FROM AUTHOR]

• The wearing effect of vehicles tires to pavement are mimicked in laboratory. • The evolution of COF of asphalt pavement in service life have been studied. • The relationship between pavement macrotexture and skid resistance during the pavement service life is investigated. • The effect of overload on the revolution of pavement skid resistance performance is summarized. To evaluate the skid resistance performance of asphalt pavement under cumulative wheel load and overload, an orthogonal test considering factors such as total traffic volume, occurrence interval, and duration of overload traffic was designed, and lab tests were conducted. This testing was performed based on the self-invented Tire-pavement Dynamic Friction Analyzer (TDFA), by which the real-time data of tire-pavement friction coefficient and pavement textures can be acquired. The results indicated that in the overall process of pavement with different gradation types, all pavement friction coefficients (COF) showed a similar trend of increasing first and then decreasing, and finally tended to be stable. In contrast, the Mean Profile Depth (MPD) values always fluctuated significantly. Moreover, it was found that there is a poor correlation between COF value and MPD value while investigating the degradation laws concerning the skid-resistance performance of asphalt pavement. Compared with the overload traffic applied in the middle and late stage of wear, the deterioration rate of pavement dynamic friction coefficient is faster and the final value of friction coefficient is lower when heavy traffic is applied in the early stage. Finally, the significance of the designed orthogonal test was analyzed. The results show that the total traffic volume has a significant impact on the COF value in the process of pavement service life, followed by the occurrence interval of heavy traffic, and finally the duration of heavy traffic. [ABSTRACT FROM AUTHOR]