ABSTRACT
Pavements for roads in cities and highways are degraded with potholes, cracking, and rutting distresses. There is a strong need to identify these locations and sections with undesired longitudinal roughness quickly and accurately every year. Traditionally, expensive standalone survey vehicles for roughness measurements and more expensive multifunction vehicles are employed by highway agencies or through contract services, which most cities and local agencies can’t afford. The primary objective of this study is to describe a low cost method to collect essential pavement condition data and share real time to expedite maintenance intervention needs. This facilitates rapid identification of pavement sections with undesired longitudinal roughness and local defects. This paper discusses the impact of social media, crowd sourcing, and advances in cheaper accurate motion sensors and cloud server data processing. These tools make it possible to develop easy-to-use low cost methods, which are affordable by city public work and smaller road agencies.
