Institute for Transportation

About the research

The selection of pavement marking materials for state and local roads is an increasingly complex and high-stakes challenge, affecting roadway safety, long-term maintenance costs, and the integration of emerging vehicle technologies. With a wide range of available materials, including paints, thermoplastics, tapes, epoxies, polyurea, and methyl methacrylate (MMA)—with each exhibiting different performance characteristics and life spans—transportation agencies struggle to determine the most effective option for specific roadway conditions. This challenge is compounded by variations in pavement surfaces, traffic volumes, climate conditions, winter maintenance practices, and installation quality, all of which influence the durability and visibility of markings. The lack of a standardized selection process has led to inconsistencies in pavement marking choices across different regions of the South Dakota Department of Transportation (SDDOT), resulting in inefficient resource allocation and unpredictable maintenance schedules.

Many agencies make decisions based on historical practices rather than objective, data-driven evaluations of performance and cost-effectiveness. This inconsistency increases the risk of premature marking failure, safety hazards, and higher long-term costs due to frequent restriping. Driver needs have been a primary driving force behind the choice of pavement marking materials and the strategies for their maintenance. The ultimate goal of pavement markings is to provide guidance and information to road users, ensuring safe and efficient travel, especially in challenging driving conditions when other visual cues are reduced. Rapid advancements in the automotive industry have given rise to new opportunities, while also challenging agencies to keep up with these changes. Driver needs have evolved to encompass both the human drivers and the machine vision/artificial intelligence (AI) systems designed to assist them. As such, the role of pavement markings in supporting Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS) cannot be overlooked. These technologies, which rely on cameras and sensors to detect lane markings, have the potential to reduce crashes caused by human error and distracted driving. However, their effectiveness is directly tied to the quality and consistency of pavement markings. Without a reliable framework for selecting and maintaining markings that meet both human and machine-readability requirements, the state risks falling behind in the transition to safer, technology-enhanced roadways.