Pavement marking retroreflectivity, a critical factor for safe driving, depends on the characteristics of both the paint and the embedded glass beads. However, traditional methods for predicting pavement marking service life often overlook these materials properties. This study investigates the influence of paint and glass bead characteristics on pavement marking retroreflectivity performance and addresses the characterization of glass bead size distribution by the coefficient of uniformity and curvature. Three field test sites on a Brazilian highway with various paint and glass bead combinations were evaluated. A statistical model, GAMLSS (Generalized Additive Model for Location, Scale, and Shape), was adjusted to evaluate the performance of the markings’ retroreflectivity as a function of paint and glass bead characteristics. The model revealed that well-graded glass beads increased retroreflectivity by around 10%, while paints with a higher volume of solids improved service life around 65%. Therefore, the results show that acrylic water-based paints with higher volumes of solids and well-graded glass beads with better shape characteristics should be preferred to improve pavement markings’ retroreflectivity and service life. The statistical model identified the key characteristics with the greatest impact on pavement marking retroreflectivity, offering valuable insights for real-world applications, which will assist pavement marking practitioners and road authorities in selecting appropriate materials to achieve enhanced durability.

Pavement markings are important features for improving road safety. As these markings must possess adequate retroreflectivity, road agencies are concerned about retroreflectivity maintenance. Consequently there is an increased focus on modeling the durability of pavement markings. Such models use time-to-failure data from life test experiments. The current study proposes a new method that consists of three steps: (i) designing an accelerated experiment for data collection; (ii) fitting a pavement marking retroreflectivity model using a generalized linear mixed model and the degradation data from the planned experiment, confirming the goodness of fit of the fitted model through the residual analysis; and (iii) conducting Monte Carlo simulation (with at least 10,000 runs of simulated vectors of the fitted model’s coefficients) to obtain the pavement marking service life distribution for a failure retroreflectivity threshold level. The simulation of service life of pavement marking provides relevant information, such as service life expectation and empirical quantities of interest (as median). The proposed method is applied to data on retroreflectivity degradation obtained from an experimental test site, a Brazilian highway with a high traffic volume, with two fixed factors (waterborne paints and glass bead application rates, both with three levels). The model indicates that retroreflectivity decreases at an average rate of 2% per day, and how materials differ from each other. The proposed model is easily implementable and can help management teams to adequately plan the maintenance time for pavement markings.

Road markings (RMs) typically consist of a paint layer and a retroreflective layer. They play a crucial role in road safety by offering visibility and guidance to drivers. Over their lifetime, dirt particles, oils, and greases are adsorbed on the RM surface, reducing their visibility and service life. A self-cleaning ability has been widely studied in several substrates. However, for RMs, this represents a breakthrough and a sustainable advance, while having the potential to increase their service life and enhance road safety. In this context, nanotechnology can be a strong ally through the application of semiconductor materials, such as TiO₂, to develop the self-cleaning ability. In addition to this novelty in RMs, quantifying this ability in terms of pollutant removal efficiency is also a challenge. In this sense, artificial intelligence (AI) and colorimetry can be combined to achieve improved results. The aims of the work herein reported were to assess the self-cleaning capability in an RM paint through the mass incorporation of semiconductors, evaluate their photocatalytic efficiency using traditional (spectrophotometric) and modern (AI-enhanced) colorimetry techniques, and compare the results obtained using both techniques. To this end, a water-based acrylic RM paint was modified through the mass incorporation of 0.5%, 1%, 2%, and 3% of nano-TiO₂, and a pollutant model widely used, Rhodamine B, was applied onto their surface. The samples were irradiated with a light source that simulates sunlight for 0, 3, 6, 12, 24, and 48 h. Visual analysis and spectrophotometric and artificial intelligence-enhanced colorimetry techniques were used and compared to evaluate the pollutant removal. The results confirm that RM paints with 2% and 3% nano-TiO₂ incorporated have a significantly higher pollutant removal ability and that both colorimetric techniques used are suitable for this assessment.

As especificações SUPERPAVE (Superior Performing Asphalt Pavements) introduziram a caracterização reológica de ligantes asfálticos, atribuindo propriedades de engenharia aos mesmos. Devido à complexidade do comportamento viscoelástico dos ligantes, os parâmetros reológicos foram inicialmente propostos apenas na região viscoelástica linear (LVER). Sabe-se que a rigidez do material é influenciada diretamente pela frequência, temperatura e envelhecimento. Esse trabalho estudou o efeito da temperatura de ensaio e do nível de envelhecimento na região viscoelástica linear durante o ensaio de varredura de deformações usando o reômetro de cisalhamento dinâmico (DSR). O envelhecimento foi realizado em estufa de filme fino rotativo (RTFO). Foram avaliados três ligantes asfálticos: um ligante convencional, um 60/85-E modificado por SBS (copolímero em bloco de estireno-butadieno-estireno) e o outro altamente modificado (HiMA). Os resultados mostram que os ligantes têm sua região viscoelástica linear reduzida com o aumento do envelhecimento e a redução da temperatura. Os ligantes modificados apresentaram maiores LVER que o ligante convencional, principalmente em altas temperaturas.

Road safety is a worldwide concern. Traffic injuries are the main cause of death for children and young people. One alternative to improve traffic safety is the enhancement of pavement markings visibility. Pavement marking efficiency depends on day and night visibility. Nighttime visibility (retroreflectivity) occurs due to the presence of glass beads. This paper compares the performance of two glass beads: G1 – Brazilian glass bead produced with recycled glass; and G2 – imported glass bead produced with new material. The research evaluated the retroreflectivity decrease of a test deck using two water-based paints from different manufacturers. The glass beads characterization process used the Computerized Optical Equipment (COE), CamSizer, and the Aggregate Image Measurement System (AIMS) to evaluate the shape, size, and gradation. Results indicated different retroreflectivity decrease trends for pavement markings with distinct glass beads, which could be associated with their shape characteristics and grain size distribution. The glass beads G1 presented the worst shape properties which lead to the poorest retroreflectivity at the test site. Thus, image characterization is helpful in estimating markings retroreflectivity prior to its application. Therefore, G1 cannot be used to substitute G2, regarding the retroreflectivity requirements in Brazil.