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

Evaluation of Skid Resistance Using CTM, DFT and SRT-3 Devices

Influence of pavement surface macrotexture on pavement skid resistance

Numerical Simulation of Tire-Pavement Interaction

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.

Pavement surface texture evaluation is mainly analyzed based on elevation data in previous research, and attention also need to be paid to wavelength information. Furthermore, a well-established relationship model between surface texture and skid resistance for real road sections still needs further investigation to help provide useful information on appropriate maintenance time considering skid resistance attenuation. In this research, the macro-texture of asphalt pavement was evaluated from different aspects, including elevation, wavelength information, and geometry, and the relationship models between the macro-texture and skid resistance (at both low and high speeds) were established and compared using the multiple linear regression (MLR) and back propagation (BP) neural network to recommend a suitable one. In order to achieve this, this study monitored anti-skidding performance and the macro-texture of six road sections for 18 months. Firstly, the Dynamic Friction Coefficient (DFC) test and core drilling were conducted on site at three different service times. Additionally, a laboratory accelerated loading test was carried out on specimens prepared by similar material composition to one of the road sections, and the British Pendulum Number (BPN) was tested after different passes of loading. Secondly, 3D laser scanning was carried out on core samples from road sections and laboratory specimens after different passes of loading. The correlation degree between macro-texture indexes and anti-skidding performance was analyzed with the grey correlation entropy analysis method. Finally, the relationship models between the anti-skidding performance at high and low speeds and macro-texture were established based on the MLR and BP neural network. The results indicate that the macro-texture indexes calculated based on elevation data to characterize vertical irregularities have a good correlation with the skid resistance despite the different service times and pavement types. Compared with the BP neural network model, the MLR model has low correlation and noticeable error. The relationship model between F60 (DFC at the speed of 60 km/h) and macro-texture could be well established by the BP neural network. In addition, the relationship between F20, BPN, and pavement surface macro-texture is poor, making it impossible to establish a model with good correlation. Generally, it is recommended to use the BP neural network to establish the relationship model between macro-texture and skid resistance.

Tennessee has been continuously engaged in skid resistance and corrective action research since 1952. A new program was initiated in July 1970 as a specific effort of inventorying the present skid resistant level of the State's primary highway system. The skid resistance level is measured with the University's two-wheel skid trailers that essentially meet the requirements of ASTM designation E 274 using the standard ASTM E 249 tire. The skid tests are performed on wetted pavements at a constant speed of 40 mph. Tests are conducted at intervals of approximately one-half mile or less in the inner wheel path of both lanes of the pavement. To date, 66 counties of the 95 counties within the State have been surveyed. This amounts to about 48 percent of the total rural highway mileage. For each test section base data on roadway goemetry, pavement surface characteristics, pavement type and date of construction, and the length of the test section are recorded for future evaluation. The results of the skid measurements are summarized in tabular form and presented graphically. The graphical form depicts the measured skid number or coefficient of friction as related to the log mile along the highway surface. This type presentation provides a continuous log of the changes in skid number throughout a particular pavement construction section. In some instances, it can be readily seen that the type of construction influences the skid resistance level. Also, variations within a construction section can be readily identified. The results of the inventory are reported systematically to the State Highway Department, and, where indicated, corrective measures are taken. The corrective action may be complete resurfacing with a hot plant mix or the application of a seal coat. Although intensive field and laboratory research has been sponsored during the past 19 years by the Highway Department, this project of inventorying all primary highway surfaces affords a systematic opportunity of pinpointing surfaces of questionable skid resistance level for corrective action. It is anticipated that the inventory and corrective action program will result in maintaining a satisfactory level of skid resistance on the roadway throughout the State and hopefully will result in the reduction of accidents. The data collected relative to characterizing the pavement surface and roadway goemetry will be useful in improving pavement design and construction techniques.

The deterioration of asphalt surface texture under traffic loading leads to a significant reduction in skid resistance and greatly impacts driving safety. However, the influence of dynamic surface texture wear on actual tyre–pavement contact remains unclear. To investigate the impact of asphalt surface texture wear on the evolution of tyre–pavement contact characteristics and their effects on skid resistance, accelerated loading wear tests were conducted and the pavement surface textures after wear were evaluated through high-resolution three-dimensional texture scanning and finite element simulation. The results indicate that asphalt pavement skid resistance decayed non-linearly with texture wear, following a logarithmic trend. Dense-graded mixtures exhibited a temporary recovery, whereas gap-graded mixtures decayed steadily. The contact area of Open Graded Friction Course (OGFC) mixtures exhibited an ‘S’-shaped evolution with wear, while mixtures with pronounced macrotexture showed lower actual contact. The Asphalt Concrete (AC) mixture exhibited the lowest adhesion coefficient and the highest load sensitivity. The multivariate regression models accurately predicted skid resistance, with interfacial adhesion remaining the primary determinant. This study provided a theoretical basis and a technical approach for the accurate prediction and long-term design of asphalt pavement skid resistance.

Chip seals are mostly constructed based on experience. However, it is difficult to evaluate the effects of pavement condition and materials type on chip seal performance based on experience only. This study used the mechanistic procedure to evaluate chip seal performance for different types of materials and pavement conditions. Millings and virgin chips are compared to evaluate whether millings can be used in chip seal. It is observed that millings provide the same strength, surface texture, and skid resistance as virgin chips. It is also observed that there is an optimum value of surface texture for which maximum strength is obtained. Cohesive resistance decreases, whereas friction coefficient, skid resistance, and texture depth after the chip seal increase with the increase of texture depth before the construction of the chip seal.

The wearing course is the top surface layer of the road. The road surface has multiple functions the main one being traffic safety, which is conditioned by skid resistance. This skid resistance is conditioned by pavement texture. This paper presents an experimental procedure allowing to evaluate surface macrotexture evolution of an asphalt concrete specimen by laboratory testing. Specimen surface changes through the application of a sinusoidal repeated load at high temperature. The studied surface is scanned before and after mechanical testing using a laser profiler. Texture maps are analysed using Abbott curve which is also called bearing ratio curve. The 3D analysis enables to quantify macrotexture evolution under repeated traffic conditions and to analyze the influence of both temperature and binder.

In order to ensure the safety of traffic, asphalt pavement is commonly required to utilize aggregates with excellent anti-abrasion property. This results in the lack of high-quality aggregates. The incorporation of solid waste in the aggregates is regarded as a high potential alternative for solving this problem. Since its material properties, such as rough surface, high Polished Stone Value (PSV) and the excellent adhesion property of asphalt, Basic Oxygen Furnace (BOF) slag can effectively improve the skid resistance of asphalt mixtures. First, the material properties of BOF slag are reviewed in this study. Then, the skid resistance of asphalt mixtures and aggregates are commendably evaluated by the Polished Stone Value test, Wehner/Schulze Tester, Aachen Polishing Machine, British Pendulum Test and Sand Patch test. The physical and mechanical properties of BOF slag play a key role in asphalt mixtures. This review found that the skid resistance mechanism of the BOF slag asphalt mixture is governed by factors such as BOF slag properties, incorporation methods and gradation types. Finally, the economic and environmental benefits of BOF slag asphalt mixtures were discussed. In addition, the function of gas catalysis and the melting of ice and snow can be added to the BOF slag asphalt mixture for a cleaner development in engineering. Furthermore, the existing problems, research directions and corresponding measures in this field are directed towards more durable and functional asphalt pavement construction.

This study aimed to analyse the attenuation law of skid resistance of steel slag asphalt mixture (SSAM) based on differential wear. In this study, an indoor accelerated wear instrument was used to accelerate the wear of the SSAM surface. A pavement laser scanner and a dynamic friction tester measured the three-dimensional morphology and dynamic friction coefficient (μ) of SSAM. Then, the improvement mechanism of steel slag on the skid resistance of SSAM was expounded by analysing the surface microtexture, mineral composition, and chemical composition of aggregates. The results showed no linear relationship between the amount of steel slag and the improvement of SSAM skid resistance. The SSAM with 50% steel slag maximised the differential wear effect and had the largest μ and the richest surface macrotexture. It was recommended that the steel slag content in the SSAM should not exceed 50%. The more mineral composition and higher average hardness of steel slag were the sources of its excellent skid resistance. In addition, it is suggested that the differential wear between mixed aggregates should be considered in the design of skid resistance pavement, and the proportion of different aggregates should be reasonably distributed.

The goal of pavement is to deliver the fine roughness and the safe road surface to traffic. It requires a secured and comfortable surface using the controlled speed of road. Through adjusting driving speed, skid resistance can be altered in one of the performances of the pavement surface. In high speed driving, there might be a certain level of risk, not in the same level as the proposed roads. Hence, this study first analyzes the speed equation under a consideration of a braking distance and then suggests the friction coefficient in high speed driving with the principle of conservation of energy. If we accept simply that the coefficient of friction is independent of speed, the difference between analysis and test value for braking distance is greatly generated. Therefore we have to analyze the coefficient of friction as an exponential function of braking speed of a vehicle.

Investigations have shown that a high skidding resistance on wet roads is associated with the presence of sharp edges in the road surface: on these sharp edges high pressures are set up which assist in breaking through the lubricating water film between tyre and road. This paper gives some details of laboratory tests now being made to investigate further the dependence of skidding resistance on such localized pressures.

Skid resistance depends on the macro- and micro-textural characteristics of pavement surface. Mean profile depth (MPD) is a widely used two-dimensional macro-texture indicator calculated from a single pavement surface profile, while pavement micro-texture is primarily affected by the characteristics of aggregates contained within the surface. In this study, twenty-two pavement sites, constructed using six common types of preventive treatments and eight typical sources of aggregates in Oklahoma, are selected as the field test beds. Pavement skid resistance and surface macro-texture data are collected in parallel at highway speeds using a grip tester and a high speed texture profiler, while aggregate properties under 3D are measured using a portable ultra-high resolution 3D laser imaging scanner. MPD values are calculated to represent surface macro-texture. Thirty-one 3D aggregate parameters in four categories (textural, feature, height, and material ratio & volume parameters) are investigated to characterise micro-texture attributes. The Pearson correlation coefficient matrix is computed within each category to exclude the parameters with strong correlations and remove their potential multi-collinearity during friction model development. Multivariate analysis is subsequently performed to examine the relationship between pavement skid resistance, and surface and aggregate texture properties. Eight texture parameters have showed statistical significance on pavement friction. Entropy (Tetp textural parameter) and peak curvature (Spc feature based parameter) present the most significant influences on pavement friction, while MPD demonstrates the least impact. The developed model based on surface and aggregate texture properties can better predict pavement friction performance. The comprehensive analysis of texture properties could assist highway agencies understanding the appropriate characterisation of aggregates and developing aggregate selection guideline for optimised skid resistance.

To supplement the research on the evaluation method of asphalt pavement texture, novel three-dimensional (3D) methods are proposed. First, pavement textures were measured in laboratory from asphalt mixture specimens using laser texture scanner (LTS), and the macro-texture and micro-texture were extracted based on spectrum analysis techniques. Then, macro-texture level evaluation indices f8mac and f9mac together with micro-texture level evaluation indices f8mic and f9mic were proposed based on the gray level co-occurrence matrix (GLCM) method, and the hyperparameters existing in GLCM were discussed. Through the correlation analysis with mean texture depth (MTD) measured by sand patch method (SPM) and friction coefficient µ measured by walking friction tester (WFT), the optimum pavement texture level evaluation indices were determined. Additionally, the evaluation index σ of distribution uniformity of pavement texture (DUPT) was proposed based on the uniformity of deviations between sub-surfaces and the average surface of pavement texture. Finally, the correlations of σ with texture profiles were studied. The results show that f8mac and f8mic are the optimum indices for pavement texture level. MTD has significant correlation with f8mac, and the correlation coefficient R is 0.9348; friction coefficient µ has significant correlation with f8mic, and the R is 0.8030. The hyperparameters of GLCM selected in this study were proved effective. Moreover, the effectiveness of σ is also validated by calibrating with standard grooved surface. It can be concluded that the proposed indices in this study are suitable to the evaluation of pavement texture level and pavement texture distribution.KeywordsHighway engineeringPavement textureGray level co-occurrence matrixThree-dimensional evaluation indexDistribution uniformity