Search Results (549)

Increasingly frequent extreme rainfall commonly leads to water accumulation on the road surface, elevating vehicle tire hydroplaning to a major threat to driving safety. Existing research mainly focused on tire model optimization or predicting critical hydroplaning speed features based on empirical formulas and numerical simulations. However, there is a lack of systematic validation of the tire–water–pavement coupling interaction under realistic pavement conditions, with particular insufficient attention paid to pavement dynamic responses. In this study, numerical simulation and field full-scale accelerated loading methods were applied to investigate dynamic response characteristics of the tire–water–pavement coupling interaction system. Parametric analyses were first performed to investigate the influences of vehicle speed, vehicle load, water-film thickness, and tire lateral position on the mechanical behaviors of the fluid–structure interaction for a moving vehicle tire. Subsequently, field-measured dynamic responses’ features were used to validate the numerical model, which was then further applied to predict critical conditions of vehicle tire hydroplaning. Finally, the mechanisms of hydroplaning and corresponding mitigation measures were discussed. The study revealed that increasing vehicle speed and water-film thickness, as well as decreasing vehicle load, would reduce the pavement supporting force. The tire–pavement contact stress and strain decreased from the vehicle tire’s center position towards its shoulders. The predicted critical hydroplaning condition suggested that increasing vehicle load mitigated hydroplaning by reducing the proportion of water-induced hydrodynamic lifting force relative to the total vehicle load. When the water depth is relatively shallow, the hydroplaning risk increases rapidly with water depth, while the water’s adverse impact on tire–pavement contact force gradually diminishes as water depth continues to increase. It implies that a vehicle with a relatively low axle load driving on the pavement with a thin thickness of retained water in light rain will still face the hydroplaning risk, as the pavement’s supporting force may be substantially reduced in this weather. The findings provide theoretical foundations and experimentally supported insights on driving safety assessment and anti-skid design of water-covered pavement. Full article

To address the challenges of winter pavement icing and the disposal of organic waste, this study developed a sustained-release deicing filler utilizing biochar derived from spent coffee grounds (SCGs). The material was synthesized through high-temperature carbonization, followed by physical adsorption of chloride salts and surface hydrophobic modification to control release rates. The study made asphalt mixtures and replaced normal mineral filler with the SCG material by volume at ratios of 0%, 50%, 75%, and 100% to test road and deicing performance. Wheel-tracking tests showed that the additive improved high-temperature stability and dynamic stability went up by 27.04% at the 75% replacement level. Salt dissolving created voids and slightly lowered water stability at high dosages, but all performance numbers still met the current engineering rules. Rutting slab tests at −5 °C showed the 100% replacement mix cut snow coverage to 11.43% in 60 min and proved it works for deicing. Pull-out tests measure the bond strength between ice and pavement at −5 °C, −7 °C, and −9 °C. The SCG deicing material weakens ice sticking and the bond strength for the 100% group at −5 °C was 0.35 kN, which is about 57.8% lower than the control asphalt. The bond strength of the deicing mix at −9 °C was still lower than the normal mix at −5 °C. This big drop in stickiness means the pavement stops ice from packing hard and makes mechanical removal easier. This study shows that the prepared deicing materials exhibit excellent sustained-release performance and snow-melting efficiency while ensuring satisfactory road performance. SCG deicing materials can effectively reduce snow accumulation on road surfaces in winter, lower the difficulty of ice-layer removal, and realize the sustainable utilization of SCGs. Full article

Surface texture plays a key role in pavement safety and performance, yet its degradation is influenced by multiple interacting factors that vary across road networks. This study developed statistical models to characterize and predict surface texture evolution on Portuguese highways using linear mixed-effects modeling. Texture measurements collected on 7204 pavement sections, each 100 m in length, over three monitoring cycles were analyzed alongside traffic, climatic, pavement structural, geometric, and spatial variables. The hierarchical structure of the data, with repeated measurements nested within pavement sections, was explicitly accounted for via random intercepts and random slopes. At the same time, temporal correlation was modeled via an autoregressive error structure. Two model specifications were evaluated: a model including only traffic and climatic variables and an extended model incorporating pavement and geometric characteristics. Results indicate that texture evolution is statistically associated with cumulative traffic loading, temperature-related indicators, precipitation, surface course type, lane position, vertical alignment, and altitude. The extended model showed a significantly better fit and superior predictive performance, as confirmed by information criteria and cross-validation metrics. The findings highlight the importance of accounting for section-level heterogeneity and roadway characteristics when modeling texture degradation. The proposed modeling framework provides a statistically scalable and robust tool for texture prediction, accounting for regional-specificities and long-term pavement management decisions. Full article

To address the shortage of natural sand and the unclear mechanism of lithology’s influence on the application of manufactured sand, this study explores the applicability of neutral rock manufactured sand in asphalt mixtures. Taking neutral diabase manufactured sand as the research object, a series of tests including the Marshall test, water stability test, high- and low-temperature stability test, and surface free energy (SFE) test were conducted to systematically analyze the effects of aggregate lithology on the volumetric indicators, road performance, and interface adhesion of asphalt mixtures. Additionally, the improvement effect of cement as an anti-stripping agent was verified. The results show that lithology of manufactured sand significantly regulates the performance of asphalt mixtures. In terms of volumetric indicators, the limestone manufactured sand mixture has the smallest void ratio (3.81%), while the diabase manufactured sand mixture has the largest (5.81%), requiring an appropriate increase in the mixing ratio of diabase manufactured sand to optimize the compaction effect. For water stability, the short-term performance ranks as diabase ≈ limestone > granite, and the long-term durability ranks as limestone > diabase > granite. A least-squares linear regression model demonstrated that the polar component of aggregate surface free energy exhibits a strong positive correlation with asphalt–aggregate adhesion work (R² = 0.92), which quantitatively explains variations in the 48 h immersed Marshall residual stability ratio among different lithologies. Regarding high-temperature stability, the order is diabase > limestone > granite. Thanks to its low crushing value and strong angularity, the diabase manufactured sand mixture achieves a dynamic stability of 12,629 times/mm at 60 °C, showing the best rutting resistance. In terms of low-temperature performance, the diabase manufactured sand mixture exhibits the optimal initial crack resistance (maximum flexural strain of 2757 με) and long-term durability (strain attenuation rate of 11.7% after 30 cycles), while the granite manufactured sand mixture fails to meet the design requirements. Adding 1.5%~2.0% cement can significantly improve the adhesion between manufactured sand and asphalt, with more obvious enhancement effects on granite and diabase, thereby optimizing water stability and high-temperature stability. The research results provide theoretical support and technical reference for the scientific selection and engineering application of fine aggregates in asphalt pavements. Full article

To enhance the comprehensive performance and interfacial adhesion of conventional emulsified asphalt, an epoxy-functionalized waterborne polyurethane modified emulsified asphalt (EFPU-MEA) was developed using an epoxy-functionalized waterborne polyurethane (EFPU) emulsion and an isocyanate curing agent. Experimental evaluations show that the EFPU-MEA achieves a tensile strength of 1.11 ± 0.05 MPa and an elongation at break of 782.5 ± 45%, demonstrating a well-balanced flexibility and deformation resistance. The interfacial bond between EFPU-MEA and aggregates exhibited robust durability under various stressors, including thermal fluctuations, low-temperature cracking, chemical corrosion, and moisture damage. Quantitative “sandwich” pull-out and shear tests determined the optimal modifier content and spraying quantity to be 15–20% and 1.0 kg/m², respectively. Under these conditions, the system maintained high bond strength following severe freeze–thaw cycles and chemical erosion. Mechanistically, fluorescence microscopy (FM) confirmed a uniform dispersion of EFPU within the asphalt matrix, providing effective physical reinforcement. Furthermore, surface free energy (SFE) analysis and Fourier Transform Infrared (FTIR) spectroscopy revealed that internal chemical crosslinking restructures the binder’s surface thermodynamics, significantly increasing the surface polarity and adhesion work. Finally, road performance tests—including marshall stability, wet track abrasion, and rutting resistance—verified the engineering durability of the EFPU-MEA mixture. These findings provide a theoretical and practical basis for the use of EFPU-MEA in extending the service life of high-grade highway pavements. Full article

Snow accumulation and ice formation can significantly reduce pavement friction, posing a serious threat to traffic safety during winter. Traditional snow-removal methods, including mechanical removal, chemical de-icing agents, and heated pavement systems, suffer from several limitations such as low efficiency, environmental impacts, and high operational costs. Electrically conductive asphalt concrete (ECAC) has therefore emerged as a promising active snow-melting technology. When an electric current passes through the conductive network formed within the asphalt mixture, heat is generated through the Joule heating effect. After incorporating conductive fillers, the electrical resistivity of ECAC mixtures can be reduced from approximately 10⁶–10⁸ Ω·cm for conventional asphalt mixtures to about 10⁻¹–10² Ω·cm. Under an applied voltage typically ranging from 30 to 60 V, ECAC pavements can increase the surface temperature by 10–30 °C within 10–30 min, thereby enabling rapid snow melting and ice removal. Meanwhile, an optimized conductive network can maintain sufficient mechanical performance, with dynamic stability generally exceeding 3000 cycles/mm. When the conductive filler content is reasonably controlled, only a limited reduction in fatigue resistance is observed. This paper presents a comprehensive review of electrically conductive asphalt concrete technologies for snow-melting pavements. The background, underlying mechanisms, material development, system configuration, and field applications of ECAC are systematically summarized. Finally, the current challenges are discussed, including the stability of conductive networks, the trade-off between electrical conductivity and pavement performance, and electrical safety. Future research directions focusing on material optimization, intelligent power control, and long-term field performance evaluation are proposed to support the practical application of ECAC pavements in sustainable winter road maintenance. Full article

The effective management of municipal road infrastructure requires up-to-date, standardized and reliable condition information to support sustainable maintenance. While visual road-condition assessment methods based on established standards are widely applied to municipal roads, they remain largely manual, time-consuming, costly and subjective. This study presents an end-to-end workflow for the automated visual inspection and condition assessment of municipal road infrastructure using high-resolution, 3D street-level imagery acquired by professional mobile mapping systems. The proposed approach integrates an efficient preprocessing pipeline for precise road-surface extraction with deep learning models trained for the specific task and an advanced postprocessing method for robust results aggregation. For this purpose, a large dataset covering approximately 352 km of municipal roads across eight municipalities was created by combining street-level imagery with expert-annotated road-condition index (RCI) values. Two neural network variants were implemented: a regression model predicting standardized RCI values and a binary classifier distinguishing between roads requiring maintenance and those in good condition. To ensure decision-oriented outputs at the infrastructure-asset level, frame-based predictions are aggregated into homogeneous road segments using outlier detection and change-point analysis along the road axis. The regression model achieved a mean absolute error of 0.48 RCI values at frame level and 0.40 RCI values at road-segment level, outperforming conventional inter-expert variability, while the binary classification model reached an F1-score of 0.85. These findings demonstrate that AI-based visual road-condition assessment using professional mobile mapping data can provide accurate, standardized and scalable condition information for municipal road infrastructure. The proposed workflow supports maintenance prioritization and infrastructure management decisions without requiring explicit detection of individual pavement defects, offering a practical pathway toward automated, cost-effective road-condition monitoring. Full article

Stone Mastic Asphalt (SMA) mixtures are widely used in high-capacity road pavements due to their durability and resistance to permanent deformation. However, although electric arc furnace (EAF) steel slag and recycled crumb rubber have been individually investigated as alternative materials in asphalt mixtures, evidence regarding their simultaneous incorporation in SMA mixtures under full-scale construction and real traffic conditions remains limited. Moreover, quantitative environmental assessments are often restricted to simplified or qualitative approaches, with limited reporting of carbon footprint results. This study investigates the combined use of electric arc furnace (EAF) steel slag aggregates and recycled crumb rubber in SMA mixtures, integrating laboratory evaluation with full-scale field application on a high-traffic motorway. Two SMA 11 mixtures were designed and assessed: one incorporating steel slag aggregates as a replacement for natural coarse aggregates, and another combining steel slag aggregates with recycled crumb rubber added through the dry process (0.8% by mixture mass). Laboratory testing included volumetric characterization, moisture sensitivity and rutting resistance, while field validation covered surface macrotexture, skid resistance, executed thickness and interlayer bonding. Both mixtures fully complied with the applicable technical specifications, achieving indirect tensile strength ratios (ITSR) above 90% and wheel-tracking slopes below 0.07 mm/10³ cycles. A simplified comparative life-cycle assessment (LCA), limited to modules A1–A3, showed a reduction in CO₂-equivalent emissions of approximately 2% for the mixture containing steel slag and up to 27% for the mixture combining steel slag and recycled crumb rubber, mainly due to the valorization of industrial by-products and end-of-life tyres. Overall, the results demonstrate the technical feasibility and potential environmental benefits of these SMA mixtures within the defined scope of laboratory verification, short-term field performance and screening LCA. The contribution of this study lies in providing applied evidence from a full-scale motorway intervention, complementing predominantly laboratory-based studies and offering a quantified environmental comparison under consistent methodological assumptions. Full article

Speed management plays a critical role in road safety; however, conventional speed limits are determined based on characteristics such as geometry and traffic volume. Limited consideration is given to the structural condition of pavements and surface distress. This study proposes an integrated mechanistic–quantitative framework that links pavement distress and road safety indicators to the selection of speed limits. A flexible pavement section on Highway No. 80 in Iraq is analyzed as a case study. Mechanistic pavement analysis using KENPAVE is employed to estimate critical strains based on field traffic data and Equivalent Single-Axle Loads (ESALs). The rate of failure is estimated by comparing ESALs and the allowable load repetitions. Safety-related constraints are then derived to quantify hydroplaning risk, braking performance through stopping sight distance, and the vertical shock criterion. The results indicate that the existing pavement structure is marginal, with a high probability of fatigue failure and sensitivity to rutting under increased traffic loads. The integrated safety analysis yields a critical wet-weather speed of approximately 67–70 km/h, while localized settlements exceeding 10 mm require speed reductions of 50–60 km/h to maintain vehicle stability. The proposed framework demonstrates that pavement conditions directly influence safe speed, providing a rational basis for safety-oriented speed management. Full article

Tire and road wear particles (TRWPs) are formed at the frictional interface of the tire and road surface and consist of polymer-containing tread with pavement mineral and binder encrustations. Their detection in various environmental compartments globally sparks increasing societal and regulatory interest. Solid quantitative information as a basis for managing and mitigating TRWPs in the environment is lacking however. This paper presents and demonstrates a model approach that produces catchment-scale terrestrial and aquatic TRWP mass balances anywhere in the world. A spatially and temporally explicit modelling method was used that builds on publicly available global datasets and process-based open-source modelling frameworks to describe hydrological processes, TRWP releases, fate and transport under a wide range of climatic conditions. High-resolution (<1 km) models were implemented and evaluated by demonstrating consistency with available field data for three watersheds on different continents. The approach provides comprehensive mass balances to underpin management of TRWPs that account for socio-economic, climate, geography and stormwater management gradients. Case study results revealed strong climate-induced differences: the fraction of vehicle-generated TRWPs exported to the estuarine environment varied between 2% (Seine watershed, France) to 18% (Yodo River watershed, Japan), corresponding to an increase in the fraction released to freshwater ecosystems from 20% to 36%, respectively. The modelling framework provides a consistent comparison between watersheds across the world. Limitations of the approach are its lack of local details and the uncertainties stemming from the still-developing scientific knowledge base. Full article

Thermal conductivity and specific heat capacity are key parameters controlling heat transfer and temperature distribution in road pavement structures. Although transient methods are increasingly used in laboratory testing, the thermal properties of asphalt mixtures have not been sufficiently studied using these methods, and no dedicated standards exist for road materials. This creates uncertainty in test procedures, specimen geometry, surface preparation, measurement location, and data interpretation, which may lead to significant errors, especially for massive and heterogeneous mixtures. The objective of this study is to systematically quantify the edge zone effect and assess its influence on the determined thermal parameters of a selected heterogeneous asphalt mixture. The study focuses on the quantitative determination of the edge zone effect, practical identification of its width in slab-shaped specimen, and the identification of scientific and practical methodological consequences, as well as the risks and limitations of applying the Modified Transient Plane Source (MTPS) method in the absence of standards. Laboratory measurements demonstrate a clear edge zone effect, with thermal conductivity and thermal diffusivity differing by up to 17% and 18%, respectively, near the specimen edges. These findings highlight the importance of methodological guidelines for slab-shaped asphalt mixture specimens and provide both scientific insight and practical guidance for the reliable application of transient method. They may also support the development of standardized testing procedures for asphalt mixtures. Full article

Reducing the environmental impact of road transport requires pavements that contribute to lower fuel consumption of vehicles and greenhouse gas emissions throughout their life cycle. Rolling resistance plays a key role in this context, while warm mix asphalt (WMA) technologies offer additional benefits by reducing energy use and emissions during production and construction. This study investigates the combined influence of aggregate type and aggregate gradation on the rolling resistance and functional performance of WMA wearing course mixtures. Ten laboratory-produced mixtures were designed, including dense-graded asphalt concrete (AC 11 VS) and stone mastic asphalt (SMA 8 S) with granite or dolomite aggregates, produced at reduced temperatures using a chemical WMA additive and polymer-modified bitumen PMB 45/80-65. Rolling resistance was evaluated using a laboratory energy loss method with two different tyres, along with assessments of volumetric properties, moisture resistance, surface macrotexture, and resistance to scuffing. The results indicate that aggregate gradation is the primary factor governing rolling resistance, and dense-graded mixtures exhibit lower energy loss due to their smoother surface texture. The aggregate type showed a secondary but consistent effect, with granite mixtures generally demonstrating slightly lower rolling resistance and improved resistance to surface degradation. In general, the findings confirm that WMA technologies can be effectively integrated into low-rolling-resistance asphalt mixtures, achieving reduced rolling resistance without compromising durability and thus supporting energy-efficient and sustainable pavement solutions. Full article

The vehicular energy consumption, primarily determined by the vehicle’s characteristics, exhibits significant variations influenced by driving behavior, traffic, and road attributes, with repercussions for emissions. This paper presents experimental results from real-traffic runs to characterize the relationship between fuel consumption and these factors. Data on consumption, performance, and kinematics of a light-duty vehicle were obtained using low-cost devices, including an On-Board Diagnostics (OBD) scanner, a unit integrating an Inertial Measurement Unit (IMU) and a Global Positioning System (GPS) receiver. The data allowed distinguishing consumption patterns between two distinct scenarios: a collector road stretch with deteriorated pavement and an express road stretch with lower surface roughness. Relevant association was identified between fuel consumption and factors such as discrete pavement anomalies and variables related to driving and traffic. Moderate correlations were observed with slope, and weaker ones with pavement roughness. Regarding the regression analysis, results identified acceleration and engine speed as the primary operational determinants of fuel consumption, with road grade emerging as the dominant geometric constraint across all scenarios. The results reveal relevant associations between fuel consumption and road, driving, and traffic-related factors while simultaneously demonstrating a robust and replicable experimental methodology based on commercially available sensing devices for real-traffic energy and emission assessments. Full article

Accurate, scalable pavement condition monitoring is essential for effective asset management, yet traditional methods of collecting metrics like the International Roughness Index (IRI), Pavement Condition Index (PCI), and Pavement Surface Evaluation and Rating (PASER) can be inefficient, expensive, and subjective. Recent efforts by Original Equipment Manufacturers have introduced crowdsourced approaches that estimate IRI at scale using connected vehicles (CVs). This study analyzes one month of CV-estimated IRI (IRI_CVe) data and compares it with manually collected PCI data from Marion County, Indiana, in 2024. The study includes four roadway classes: primary arterial, secondary arterial, primary collector, and local street, with 562, 147, 426, and 2402 centerline miles of data, respectively. IRI_CVe coverage was nearly complete for arterial and collector roads (93–100%) but was limited for local streets (37%). Threshold optimization revealed that the “needs maintenance” IRI category (IRI > 170 in/mi) correlates most strongly with PCI values below 50. The study found that 68%, 65%, 70%, and 59% of the roadway segments had PCI and IRI classifications in agreement. Spatial and categorical comparisons suggest some systematic biases between the metrics across roadway types, reflecting how they measure different dimensions of pavement condition. The results demonstrate near-term applications of IRI_CVe data for quality control in PCI-based asset management and support practical guidelines for integrating complementary pavement assessment metrics. Full article

To evaluate the cracking characteristics of asphalt pavements under thermal stresses, the finite element (FE) software ABAQUS 2021 was used in this paper to establish thermal and mechanical parameter models, respectively. The temperature field distributions in winter and summer were analyzed according to the actual situation based on fracture mechanics theory and the extended FE method, as well as the most unfavorable crack type for crack propagation was also studied. Further, the impact of the propagation of transverse cracks on the road surface was investigated by changing the solar radiation, sunshine duration, and wind speed. Finally, the propagation pattern of reflective cracks was observed under the cyclic temperature field. The results show that under the action of the temperature field alone, type I cracks, which are cracks that undergo opening displacement due to the vertical tensile stress acting on the crack surface, are the main type of cracks, while the trend of crack propagation was much higher in winter than in summer. It was also found that changing the parameters of solar radiation, sunshine duration, and wind speed could significantly impact cracking. Under the cyclic temperature field, the length of reflective cracks was proportional to time, and the initial crack length significantly affected the pavement life. Therefore, pavement inspection should be more stringent in winter, and initial cracks should be avoided as much as possible during paving. Full article