This study addresses the critical need for automated and reliable road marking maintenance to support both human drivers and Automated Vehicle (AV) systems . Traditional methods often require manual inspection or specialized vehicles; this paper proposes a more dynamic approach using computer vision. Key Research Objectives
: Utilizing advanced algorithms to analyze road imagery in real-time to identify wear and tear without interrupting traffic flow. Significance in Transportation 125956
As semi-autonomous and autonomous vehicles become more common, the visibility of road markings serves as a fundamental infrastructure requirement. This paper provides a framework for maintaining these standards efficiently through automated detection. This study addresses the critical need for automated
: Focusing on the percentage of residual marking (PRM) and the contrast between the marking and the surrounding road surface as primary indicators of quality. : Evaluating road markings based on characteristics that
: Evaluating road markings based on characteristics that impact visibility for human eyes and machine sensors.