Search Results (15)

The characteristics of pavement texture are key determinants of skid resistance, directly affecting tire-pavement interactions. This study examines the relationship between separated pavement textures and friction coefficients under dry and wet conditions. Using 3D laser scanning, texture data were collected from 40 asphalt pavement sections in Nanchang. The data were processed through Fourier Transform and Butterworth filtering, enabling separation of macro- and micro-textures. Based on ISO 25178-2, 16 parameters—including S_a (Arithmetic Mean Height), S_tr (Texture Aspect Ratio), V_mc (Core Material Volume), and S_sk (Skewness)—were selected to represent macro- and micro-texture features. These parameters were analyzed against dry and wet friction coefficients, and regression models were developed to predict F_Dry and F_Wet. The results show significant effects of both macro- and micro-texture parameters on friction coefficients. Among macro-texture parameters, S_a and V_mc strongly correlate with F_Dry, suggesting that greater surface roughness and core material volume enhance friction in dry conditions. Conversely, S_sk negatively correlates with F_Dry, indicating that negatively skewed profiles improve skid resistance. Other macro-texture parameters also influence F_Dry to varying extents. For micro-texture, S_dc (Material Height Difference), S_pd (Peak Density), and V_vv (Valley Void Volume) primarily affect F_Wet, with all showing significant positive correlations. This indicates that sharp peaks and void structures in micro-texture enhance skid resistance in wet conditions. The regression models effectively predict both friction coefficients, reducing field testing complexity and cost. These models provide an efficient tool for evaluating skid resistance and supporting pavement performance and maintenance management. This study highlights the distinct roles of macro and micro-texture in skid resistance, offering insights for optimizing pavement design and maintenance. Full article

This study proposes a non-contact framework for evaluating the skid resistance of shared roadside pavements to improve cyclist and pedestrian safety. By integrating a friction tester and a laser scanner, we synchronize high-resolution three-dimensional (3D) surface texture characterization with friction coefficient measurements under dry and wet conditions. Key metrics—including fractal dimension (FD), macro/micro-texture depth density (HL_TX and WL_TX), mean texture depth (MTD), and joint dimensions—were derived from 3D laser scans. A hierarchical regression analysis was employed to prioritize the influence of texture and joint parameters on skid resistance across environmental conditions. Combined with material types (brick, tile, and stone) and drainage performance, these metrics are systematically analyzed to quantify their correlations with skid resistance. Results indicate that raised macro-textures and high FD (>2.5) significantly enhance dry-condition skid resistance, whereas recessed textures degrade performance. The hierarchical model further reveals that FD and MTD dominate dry friction (β = 0.61 and −0.53, respectively), while micro-texture density (WL_TX) and seam depth are critical predictors of wet skid resistance (β = −0.76 and 0.31). In wet environments, skid resistance is dominated by micro-texture density (WL_TX < 3500) and macro-texture-driven water displacement, with higher WL_TX values indicating denser micro-textures that impede drainage. The study validates that non-contact laser scanning enables efficient mapping of critical texture data (e.g., pore connectivity, joint depth ≥0.25 mm) and friction properties, supporting rapid large-scale pavement assessments. These findings establish a data-driven linkage between measurable surface indicators (texture, morphometry, drainage) and skid resistance, offering a practical foundation for proactive sidewalk safety management, especially in high-risk areas. Future work should focus on refining predictive models through multi-sensor fusion and standardized design guidelines. Full article

Runway skid resistance is crucial for the safety of aircrafts. Despite being internationally regulated, investigation reports published by the Australian Transport Safety Bureau and the US National Transportation Safety Board indicate that 4.9–22% of runway excursion accidents are related to insufficient friction, or to friction overestimation. Consequently, based on this review of friction physics, aircraft accident reports, international runway surface regulation, and aircraft braking performance regulation, it was concluded that significant improvement in the management of runway surface characteristics can be achieved. Areas for potential improvement in the current systems for aircraft skid resistance include gaps in the operational reporting of prevailing runway contamination, as well as friction and surface texture measurement and interpretation protocols. Furthermore, aircraft braking performance regulations are not related to actual runway surface friction levels, resulting in reportedly good runways being found to provide inadequate aircraft skid resistance in certain conditions. Recommendations include improvements in the management of runway friction and texture measurement and analysis during pavement design, and through the service life of the pavement surfaces. Finally, the basis of an improved international runway surface engineering design and management system is outlined. Recommendations can reduce the risk of aircraft skidding accidents in the future. Full article

Effective management of airport pavements is essential for maintaining safety and operational efficiency in air travel. An airport pavement management system (APMS) operates at two levels: the network level, which monitors overall pavement performance across the airport, and the project level, which conducts detailed inspections of individual pavements. However, pavement assessments are often costly and labor intensive, necessitating the development of cost-effective and practical models. This paper introduces the Airport Pavement Integrated Risk Management (APIRM) model, which integrates pavement condition assessment criteria with safety risk management (SRM) methodologies. The model was applied at Istanbul Airport. By using APIRM, airports can prioritize high-risk areas, optimizing resource allocation and enhancing safety. The model encourages coordination among various airport departments, offering a holistic approach to pavement management that integrates maintenance requirements with safety considerations. Full article

Unlike other pavement indices, the skid resistance, or friction, of bituminous pavements behaves differently. After the extension of a new layer, the friction increases as the bitumen film is removed and the aggregates are exposed. The aggregates are then polished by traffic, mainly by heavy vehicles, and the pavement reaches the seasonal phase, in which, if heavy traffic volume remains constant, the only variations are seasonal, with maximum values in winter and minimum values in summer. Nonetheless, in tunnels, as they are not exposed to climatic actions, the friction value is lower than outside. Therefore, the article evaluates the skid resistance decrease in tunnels compared to outdoor conditions. For this purpose, the skid resistance values in dual-carriageway tunnels in Gipuzkoa (Spain) were studied and compared with the values obtained 500 m before and after the tunnel. Overall, a 10% friction decrease was observed inside the tunnels. In winter, the decrease was 11%, while in summer it was 8%. In tunnels longer than 500 m, the decrease was greater (12%) than in tunnels shorter than 500 m (9% and 7%). This analysis contributes to a better knowledge of the available friction inside a tunnel and to the better management of road safety. Full article

Runway surface friction is critically important to safe aircraft operations and mostly depends on the surface texture, which provides grip in the presence of contamination and directly affects the friction coefficient in general. Microtexture assessment is the most challenging part of texture assessment since there is no standardised pavement microtexture control method in runway maintenance and management practice. The purpose of this study was to develop a simple laser profilometer and analysis model and subsequent validation for use in runway friction surveys. To that end, a simple laser profilometer was developed, and a profile picture analysis and macrotexture filtration method were designed. Test results were compared to the stylus-based roughness tester and the British Pendulum Tester. The proposed profile picture analysis and profile smothering and filtration methodology, based on linear approximation, is simpler and more effective for the case of macrotexture filtration for the friction survey. The laser profilometer model results were highly correlated with the stylus-based roughness tester results (R² = 0.99). The average roughness of the microtexture profile, after smothering and macrotexture filtration, also showed good correlation with the British Pendulum results (R² = 0.78). The results from this study confirm the possibility of texture assessment for routine runway friction surveys using a simple and economical laser profilometer, which is not routinely available in current airport surface friction management. Full article

Accurate assessment of road pavement friction is crucial for maintaining road safety. This study explores the prediction of the friction coefficient (µ) using 3D texture parameters of pavement surfaces. Measurements were conducted on 17 different rural road sections using the Traction Watcher One (TWO) for friction coefficients and a newly developed Static Road Scanner (SRS) for surface texture. Multiple linear regression models were created, incorporating texture parameters such as the valley material portion (S_mr2,MIC), arithmetic mean peak curvature (S_pc,MAC), and dale void volume (V_vv,PS). The results demonstrate a strong correlation between texture characteristics and friction, with R² values up to 0.80 and an RMSE as low as 0.076, validating the model’s accuracy. This approach highlights the potential of using non-contact texture measurements for reliable prediction of friction, offering a significant advancement in pavement management and safety. Full article

Pavement friction plays a crucial role in ensuring the safety of road networks. Accurately assessing friction levels is vital for effective pavement maintenance and for the development of management strategies employed by state highway agencies. Traditionally, friction evaluations have been conducted on a case-by-case basis, focusing on specific road sections. However, this approach fails to provide a comprehensive assessment of friction conditions across the entire road network. This paper introduces a hybrid clustering algorithm, namely the combination of density-based spatial clustering of applications with noise (DBSCAN) and Gaussian mixture model (GMM), to perform pavement-friction performance ratings across a statewide road network. A large, safety-oriented dataset is first generated based on the attributes possibly contributing to friction-related crashes. One-, two-, and multi-dimensional clustering analyses are performed to rate pavement friction. After using the Chi-square test, six ratings were identified and validated. These ratings are categorized as (0, 20], (20, 25], (25, 35], (35, 50], (50, 70], and (70, ∞). By effectively capturing the hidden, intricate patterns within the integrated, complex dataset and prioritizing friction-related safety attributes, the hybrid clustering algorithm can produce pavement-friction ratings that align effectively with the current practices of the Indiana Department of Transportation (INDOT) in friction management. Full article

Traditionally, pavement safety performance in terms of texture, friction, and hydroplaning speed are measured separately via different devices with various limitations. This study explores the feasibility of using a novel 0.1 mm 3D Safety Sensor for pavement safety evaluation in a non-contact and continuous manner with a single hardware sensor. The 0.1 mm 3D images were collected for pavement safety measurement from 12 asphalt concrete (AC) and Portland cement concrete (PCC) field sites with various texture characteristics. The results indicate that the Safety Sensor was able to measure pavement texture data as traditional devices do with better repeatability. Moreover, pavement friction numbers can be estimated using 0.1 mm 3D data via the proposed 3D texture parameters with good accuracy using an artificial neural network, especially for asphalt pavement. Lastly, a case study of pavement hydroplaning speed prediction was performed using the Safety Sensor. The results demonstrate the potential of using ultra high-resolution 3D imaging to measure pavement safety, including texture, friction, and hydroplaning, in a non-contact, continuous, and accurate manner. Full article

Very thin asphalt overlays (VTAOs) have been widely used as a cost-effective preventive maintenance measure in various countries. However, because of the complex combinations of aggregate gradations and asphalt materials, the selection of VTAOs is an unsolved problem that is extremely important for pavement management authorities. Therefore, this study proposed a comprehensive evaluation method for VTAOs based on the analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS). Three VTAO mixtures comprising different aggregate gradations (stone mastic asphalt (SMA), open-graded friction course (OGFC), and asphalt concrete (AC)) and different asphalt materials (organic silicon (OS) and styrene-butadiene-styrene (SBS)) were investigated and preliminarily compared in the laboratory. Subsequently, four road performance indicators (pavement condition indicator, British pendulum number, texture depth, and international roughness index) were selected as the evaluation indices, and their weights were calculated using the AHP according to the questionnaires collected from specialists. Finally, the field test data of the road performance indicators with scale confusion were handled using TOPSIS, and the closeness was considered as the final evaluation criterion. The results indicated that the mixture of AC and SBS exhibited the best performance among the three investigated mixtures. Categorizing the evaluation indicators into two aspects—the strength aspect and the structural aspect—it is found that the strength aspect of a VTAO is mainly affected by the asphalt materials, whereas the structural aspect of a VTAO is mainly affected by the aggregate gradation. This study provides a practical method for evaluating the road performance of VTAO with diverse measurement indices, as well as a quantitative scope for the impacts of the aggregate gradation and asphalt materials on the road performance. Full article

Pavement friction is an important topic addressed by transportation agencies to reduce the number of traffic crashes and fatalities caused by poor friction between tires and pavement surface. Pavement friction management (PFM) provides the essential tools and techniques to effectively evaluate pavement friction conditions and provide informed maintenance decisions using surface treatments. State Departments of Transportation (DOTs) utilize various engineering practices to collect and analyze friction-related data, crash data, and traffic data. In addition, state DOTs tend to employ different techniques and policies to manage the pavement friction depending on budget levels, strategic objectives, and climate conditions. Due to these diversified practices in friction management, in this study, we intend to provide a comprehensive review of the state of the practice among state DOTs. Online surveys were analyzed using descriptive and statistical correlation analyses to study the experience of state DOTs with managing pavement friction, considering feedback from 32 state DOTs in the USA. Exploring the methods to manage the pavement friction used by state agencies will help researchers and officials know more about the strategies towards an effective PFM. It also presents opportunities to enhance the approaches of the followed programs and highlight the gaps of the current practices. The results obtained from the survey identify the practical policies and propose future enhancements to maximize the value of pavement assets and promote safety. Full article

Skid resistance is a significant feature that provides consistent traffic safety management for road pavements. An appropriate level of Skid resistance describes the contribution that the pavement surface makes to tire/road friction, and the surface of the road pavement can reduce vehicle operation cost, traffic accidents, and fatalities, particularly in wet conditions. Wet conditions decrease the level of the skid resistance (pavement friction), and this may lead to serious struggles related to driving on the road pavement (e.g., skidding or hydroplaning), which contributes to higher crash rates. The knowledge of skid resistance is essential to ensure reliable traffic management in transportation systems. Thus, a suitable methodology of skid resistance measurement and the understanding of the characterization of the road pavement are key to allow safe driving conditions. This paper presents a critical review on the current state of the art of the research conducted on skid resistance measurement techniques, taking into account field-based and laboratory-based methodologies, and novel road sensors with regard to various practices of skid resistance, factors influencing the skid resistance, the concept of the minimum skid resistance and thresholds. In conclusion, new trends that are relevant to data collection approaches and innovative procedures to further describe the data treatment are discussed to achieve better understanding, more accurate data interoperability, and proper measurement of skid resistance. Full article

The development of a linear mixed model to describe the degradation of friction on flexible road pavements to be included in pavement management systems is the aim of this study. It also aims at showing that, at the network level, factors such as temperature, rainfall, hypsometry, type of layer, and geometric alignment features may influence the degradation of friction throughout time. A dataset from six districts of Portugal with 7204 sections was made available by the Ascendi Concession highway network. Linear mixed models with random effects in the intercept were developed for the two-level and three-level datasets involving time, section and district. While the three-level models are region-specific, the two-level models offer the possibility to be adopted to other areas. For both levels, two approaches were made: One integrating into the model only the variables inherent to traffic and climate conditions and the other including also the factors intrinsic to the highway characteristics. The prediction accuracy of the model was improved when the variables hypsometry, geometrical features, and type of layer were considered. Therefore, accurate predictions for friction evolution throughout time are available to assist the network manager to optimize the overall level of road safety. Full article

The evaluation of friction is a key factor in monitoring and controlling runway surface characteristics. For this reason, specific airport management and maintenance are required to continuously monitor the performance characteristics needed to guarantee an adequate level of safety and functionality. In this regard, the authors conducted years of experimental surveys at airports including Lamezia Terme International Airport. The surveys aimed to monitor air traffic, features of geometric infrastructure, the typological and physical/mechanical characteristics of pavement layers, and runway maintenance planning. The main objective of this study was to calibrate specific models to examine the evolution of friction decay on runways in relation to traffic loads. The reliability of the models was demonstrated in the light of the significance of the friction measurement patterns by learning algorithms and considering the traffic data by varying the geometric and performance characteristics of the aircraft. The calibrated models can be implemented into pavement management systems to predict runway friction degradation, based on aircraft loads during the lifetime of the surface layers of the pavement. It is thus possible to schedule the maintenance activities necessary to ensure the safety of landing and takeoff maneuvers. Full article

(1) Run-off-road (ROR) crashes are a crucial issue worldwide, resulting in a disproportionate number of traffic deaths. In safety research, macro-level analysis on large datasets is usually conducted by linking explanatory variables to ROR crash frequency/severity. Micro-analysis approaches, like the one used in this study, are instead less frequent. (2) A comprehensive Italian Fatal + Injury (FI) crash dataset was filtered to identify two-way two-lane rural road curves on the national road network on which more than one ROR FI crash (i.e., at least two crashes) in the observation period of four years had occurred. The typical features of the ROR FI crashes and the recurrent geometric (characteristics of tangents and curves) and operational features (inferred speeds, acceleration/decelerations) of the crash sites were reconstructed. (3) The main contributory factors in ROR FI crashes are: wet pavements, speeding, and distraction. Sites with a relevant history of ROR FI crashes present recurrent safety issues such as inadequate horizontal curve coordination, an insufficient tangent length for decelerating, and inferred operating speeds comparable/higher than the inferred design speeds. (4) Based on findings, some practical suggestions for road safety management and maintenance are proposed through specific indicators and countermeasures (speed, perception, and friction related). Full article