An Original Evaluation of the Wearing Course Macrotexture Evolution using the Abbot Curve

Cement concrete pavements are crucial to urban infrastructure, significantly influencing road safety and environmental sustainability with their anti-skid and noise reduction properties. However, while texturing techniques like transverse grooving have been widely adopted to enhance skid resistance, they may inadvertently increase road noise. This study addressed the critical need to optimize pavement textures to balance improved skid resistance with noise reduction. Tests were conducted to assess the influence of surface texture on skid resistance and noise, exploring the relationship between texture attributes and their performance in these areas. The investigation examined the effects of texture representation methods, mean profile depth, and the high-speed sideway force coefficient (SFC) on noise intensity and pavement skid resistance. The findings revealed that transverse grooves significantly improved the SFC, enhancing skid resistance. In contrast, longitudinal burlap drag, through its micro- and macro-texture adjustments, effectively reduced vibration frequencies between the tire and pavement, thus mitigating noise. Utilizing the TOPSIS multi-objective optimization framework, an optimization model for pavement textures was developed to augment skid resistance and noise reduction at varying speeds. The results indicated that at 60 km/h, an optimal balance of groove width, depth, and spacing yielded superior skid resistance with a minimal noise increase. At 80 km/h, increased groove spacing and depth were shown to effectively decrease noise while maintaining efficient water evacuation. The optimal pavement texture design must consider the specific context, including traffic volume, vehicle types, and operating speeds. This study provides essential guidance for optimizing urban cement concrete pavement textures, aiming to diminish traffic noise and bolster road safety.

To preserve the existing asphalt pavement and extend its service life, various preventive maintenance methods, such as chip seal, slurry seal, fog seal, and microsurfacing, have been commonly applied. Sand fog seal is one of such maintenance methods, which is based on the application of bitumen emulsion and sand. Thus, its performance is largely dependent on the properties of the bitumen emulsion and sand. This study aims to develop an improved sand fog seal method by using waterborne epoxy resin as an emulsion modifier. To this end, both laboratory tests and field trials were conducted. In the laboratory, the wet track abrasion and British pendulum test were performed to determine the optimum sand size for the sand fog seal, and the rubbing test was carried out to evaluate the wearing resistance of the sealing material. In the field, pavement surface regularity before and after the sand fog seal application was measured using the 3 m straightedge method, and the surface macrotexture and skid resistance were evaluated with the sand patch method and British pendulum test, respectively. The laboratory test results indicated that the optimum sand size range is 0.45–0.9 mm, and the sand fog seal with waterborne epoxy resin showed good wearing resistance and skid resistance. The field test results verified that both the pavement texture and skid resistance were substantially improved after sand fog sealing.

Pavement skid resistance is commonly predicted from its statistical relationships with pavement texture indices, under the assumption of isotropic skid resistance and textural characteristics. The assumptions are incorrect because both skid resistance and surface texture of in-service pavements exhibit directional characteristics caused by uni-directional traffic polishing. This paper proposes a new approach for predicting directional skid resistance based on directional characteristics of pavement texture. Skid resistance and laser images of surface texture were measured from in-service pavements. Statistical equations were derived to relate directional texture indices with the corresponding skid resistance in the same direction. The results clearly indicated that, compared with the traditional method, the new approach produced significantly more correct and accurate predictions of in-service pavement skid resistance.

Skid resistance of road surfaces depends mostly on pavement texture. This texture is usually divided to two components: microtexture and macrotexture. Microtexture refers to the small-scale texture of the road aggregate component while macrotexture refers to the large-scale texture of the road as a whole due to the aggregate particle arrangement. Both components contribute to the generation of friction between tyre and road. However, due to traffic, the first-cited component is continuously polished over the road's life. Maintaining that microtexture depends greatly on the aggregates used in the wearing course, the traffic level and the vehicle velocities. This work tries to quantify the influence of these three parameters on skid resistance degradation. Different specimens fabricated from different types of aggregates are submitted to different polishing pressure levels and velocities. From experimental results, an updated version of an existing model of skid resistance evolution is thereby proposed and validated. As a possible application of the new model, a prediction of damages induced by truck and passenger car traffic on skid resistance is proposed.

RETRACTED: Abrasion and skid resistance of concrete containing waste polypropylene fibers and palm oil fuel ash as pavement material

Preliminary study on the correlation between two-dimension surface texture and friction

Investigation to the skid resistance of asphalt pavement based on the movement of aeolian sand

Water on road surfaces significantly degrades the available skid resistance. Indeed, 25% of injury accidents occur on wet roads in France due to lack of skid resistance. Some research results advocate an exponential decrease in skid resistance with increase in water depth. The above conclusions show the importance of knowing the water depth present on road surfaces during and after rainfall events in order to evaluate the available skid resistance for driver safety. In this paper, a prediction model of water depth on road surfaces during and after rainfall events is presented. This model takes into account the road surface characteristics such as macrotexture, slope and porosity, and weather conditions such as temperature, wind speed, relative humidity and rainfall rate. The model is based on the kinematic wave simplification of the Saint Venant equations, which represents the balance of flows from rainfall, run-off, infiltration and evaporation. The model is validated from comparisons to experimental measurements of water depth performed on four different surfaces of the IFSTTAR test track. The experimental device for the validation is composed of sensors that measure water depth, rainfall intensity, wind velocity, air humidity and temperatures. The model predictions on these four surfaces are very satisfactory.

Pavement texture polishing under vehicle loads is the main cause of skid resistance degradation. For Portland cement concrete (PCC) pavement, the repeated vehicle load is directly borne by the surface mortar. However, no standardized polishing method exists to characterize the skid resistance degradation of the surface mortar, and the mechanism of the texture evolution and skid resistance degradation during polishing remains unclear. In this study, the 3D topography scanning and the British pendulum tester were utilized to investigate the texture evolution of the surface mortar and its impact on skid resistance during accelerated polishing. A multi-scale analysis method based on the bearing area curve (BAC) and power spectral density (PSD) analysis was proposed. The relationship between the surface mortar texture and British pendulum number (BPN) under dry and wet conditions was established. The results indicate that the high-frequency texture of the surface mortar exhibits a non-uniform vertical distribution. The top topography corresponding at 10% material ratio (mr) shows the strongest correlation with BPN under dry conditions. For wet conditions, the texture with wavelengths λ > 0.25 mm provided by fine aggregates is key to enhancing the skid resistance. The findings provide a theoretical basis and technical guide for PCC pavement texture optimization.

Roughness of the road surface acts as an obstacle for the vehicle wheel slip on the road surface especially in wet conditions. Road surface roughness can be generated from the properties of the aggregate or bitumen as a characteristic of asphalt mixture. Various types of added material have been used to improve the performance of hot mix asphalt mixture as well as the warm mix asphalt. The addition of BNA-R and zeolite on the warm asphalt mixtures has been investigated, particularly related with its effect on the value of the skid surface due to the wheels track of the vehicle. The study was conducted in an asphalt mixture before and after the traversed wheel condition. In this study, 7.560 trajectory path using the Wheel Tracking Machine and skid resistance test using a modified British Pendulum Tester, were conducted. Skid resistance test involved various temperatures on the surface of the specimen. The results showed that the addition of BNA-R can increase the value of the skid at the beginning of the track, but at the last track, skid resistance performance was stagnant. Zeolite additive material in warm mix asphalt has improved skid resistance, especially the resistance of asphalt concrete mixture to temperature changes.

Present article reviews the early and recent developments in skid resistance measurement techniques at asphalt concrete pavement. Suitability and limitations of various methods used for capturing skid characteristics of the surface has been outlined. The harmonization of laboratory and field-testing methods has been summarized briefly. Harmonization is agreement of test outcomes reported from field as well as laboratory. Correlation analysis of various in-situ and laboratory test data has been made to maintain the better harmony of measurement either in field or in laboratory. Measurement of skid resistance in field is time consuming, labor intensive and requires use of costly, advanced and sophisticated instruments. Lab measurement lags in accuracy and still needs improvement in design and working methodology which compelled researchers for looking into modelling as an alternative option. In the subsequent sections, progress in modelling approach (analytical to numerical) has been discussed in brief. Analytical and numerical solutions of asphalt concrete pavement for modelling skid resistance have been reviewed and emphasis for choosing a particular solution has been justified on the basis of accuracy as well as efficacy of the output model. Critical factors affecting skid resistance model like hydroplaning, tire related parameters, temperature, surface texture has been highlighted in this manuscript. Skid data obtained from any model whether it is analytical or numerical, needs to be validated against field measurement or some established data. Validation of skid resistance model using field test and experimentally derived equations in various research studies has been summarized in later section of this article. Few key research directions have been suggested as scope of future study so as to predict a more reliable skid resistance model (1) For predicting dynamic frictional properties with higher accuracy at tire pavement interface, tire pavement interaction modelling still needs improvement considering all field constraints (2) Influence of surface texture, hydroplaning, temperature and pavement ageing needs to be studied in depth for modelling skid resistance as these are critical parameters & contributes significantly.

Skid resistance, or friction, on a road surface is a critical parameter in functional highway assessments, given its direct relationships with safety and accident frequency. Therefore, road administrations must collect friction data across their road networks to ensure safe roads for users. In addition, having a predictive model of skid resistance for each road section is essential for an efficient pavement management system (PMS). Traditionally, road authorities disregard rural roads, since they are more focused on freeways and traffic-intense roads. This study develops a model for predicting minimum-available skid resistance, which occurs in summer, measured using the Sideway-force Coefficient Routine Investigation Machine (SCRIM), on bituminous pavements in the single-carriageway road network of the Province of Gipuzkoa, Spain. To this end, traffic volume data available in the PMS of the Provincial Council of Gipuzkoa, such as the annual average daily traffic (AADT) and the AADT of heavy vehicles (AADT.HV), were uniquely used to forecast skid-resistance values collected in summer. Additionally, a methodology for eliminating outliers is proposed. Despite the simplicity of the model, which does not include information about the materials at the surface layer, a coefficient of determination (R2) of 0.439 was achieved. This model can help road authorities identify the roads for which lower skid-resistance values are most likely to occur, allowing them to focus their attention and efforts on these roads, which are key infrastructure in rural areas.

Influence of pavement surface macrotexture on pavement skid resistance

Evaluate asphalt pavement frictional characteristics based on IGWO-NGBoost using 3D macro-texture data

In recent years, ultra-thin wearing course asphalt mixture has been widely used in the reconstruction of old road surfaces and the functional layer of new road surfaces due to its good road performance. To improve the rutting resistance of ultra-thin wearing course asphalt mixture, this research presents an Ultra-thin Wearing Course-10 (UTWC-10) asphalt mixture with good high-temperature stability and skid resistance based on the Taylor system standard mesh specifications. The Course Aggregate Void Filling (CAVF) method is used to design the UTWC-10 asphalt mixture, which is compared with two other traditional ultra-thin wearing course asphalt mixtures on the basis of different laboratory performance tests. The high-temperature rutting test data shows that the rutting dynamic stability (DS) index of the UTWC-10 asphalt mixture is much higher than that of traditional wearing course asphalt mixtures, as it has better high-temperature stability. Moreover, anti-sliding performance attenuation tests are conducted by a coarse aggregate polishing machine. The wear test results show that the skid resistance of the UTWC-10 asphalt mixture is promising. The anti-sliding performance attenuation test can effectively reflect the skid resistance attenuation trend of asphalt pavement at the long-term vehicle load. It is verified that the designed UTWC-10 asphalt mixture shows excellent high-temperature rutting resistance and skid resistance, as well as better low temperature crack resistance and water stability than the traditional wearing course asphalt mixtures.