Model for Predicting Road Markings Service Life

Babić, Dario; Ščukanec, Anđelko; Babić, Darko; Fiolić, Mario · 2019 · Crossref

DOI: 10.7250/bjrbe.2019-14.447

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Summary

This study addresses the critical need for optimizing road marking maintenance to ensure driver safety and reduce infrastructure costs. Road markings are essential for visual guidance, but their effectiveness depends on maintaining adequate retroreflectivity, particularly at night. The authors aim to develop predictive models for the service life of three common road marking materials: solvent-borne paint, thermoplastic, and agglomerate cold plastic. The research is motivated by the limitations of previous models, which often relied on static measurement methods, had low accuracy, or failed to account for key degradation factors such as winter maintenance activities. The methodology involved a large-scale data collection effort across Croatia, analyzing 115 roads with solvent-borne paint (5,218 km), 30 roads with thermoplastic markings (579 km), and 30 roads with agglomerate cold plastic markings (498 km). Retroreflectivity was measured using a dynamic method, which provides continuous data along the entire road section, at two specific intervals: shortly after renewal (30–60 days) and after the winter season. This approach, conducted between 2011 and 2015, allowed for the assessment of degradation over time. The study incorporated several independent variables known to affect service life, including initial retroreflectivity, road marking age, position (center vs. edge), annual average daily traffic (AADT), average speed limit, and the intensity of winter maintenance activities (snowplough passes). Multiple regression analysis was used to determine the statistical significance of these factors and to construct predictive models for each material type. The results indicate that initial retroreflectivity, road marking age, position, and winter maintenance activity were statistically significant predictors for solvent-borne paint degradation. The developed models for all three materials demonstrated satisfactory accuracy when tested against new data sets. Descriptive statistics revealed that agglomerate cold plastics maintained the highest retroreflectivity levels both after renewal and after winter, followed by thermoplastics, while solvent-borne paint exhibited the lowest values. The models successfully quantified the impact of specific factors, such as the reduction in retroreflectivity caused by snowplough activity, providing a more comprehensive understanding of material degradation than previous studies. The significance of this research lies in its contribution to road asset management and traffic safety. By providing accurate, data-driven models for predicting service life, road authorities can optimize maintenance schedules, ensuring that markings remain visible while minimizing unnecessary renewal costs. This study is notable for being the first large-scale research to use dynamic measurement methods for this purpose and for developing the first available model for agglomerate cold plastic road markings. The findings offer a practical tool for rationalizing maintenance activities and improving the overall safety of road infrastructure.

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• signage environment