Unmanned Aircraft Systems in Road Assessment: A Novel Approach to the Pavement Condition Index and VIZIR Methodologies

Abstract

This paper presents an innovative approach to road assessment, focusing on enhancing the Pavement Condition Index (PCI) and Visión Inspection de Zones et Itinéraires Á Risque (VIZIR) methodologies by integrating Unmanned Aircraft System (UAS) technology. The research was conducted in an urban setting, utilizing a UAS to capture high-resolution imagery, which was subsequently processed to generate detailed orthomosaics of road surfaces. This study critically analyzed the discrepancies between traditional field measurements and UAS-derived data in pavement condition assessment. The study findings demonstrate that photogrammetry-derived data from UAS offer at least similar or, in some cases, improved information on the collection of a comprehensive state of roadways, particularly in local and collector roads. Furthermore, this study proposed key modifications to the existing methodologies, including dividing the road network into segments for more precise and relevant data collection. These enhancements aim to address the limitations of current practices in capturing the diverse and dynamic conditions of urban infrastructure. Integrating UAS technology improves the measurement of pavement condition assessments and offers a more efficient, cost-effective, and scalable approach to urban infrastructure management. The implications of this study are significant for urban planners and policymakers, providing a robust framework for future infrastructure assessment and maintenance strategies.

Keywords

• pavement condition index
• VIZIR
• PCI
• pavement assessment
• UAS
• drone inspection