How can agencies leverage technology (e.g., drones, sensors) to improve pavement condition assessment and data collection?

Agencies can leverage various technologies to improve the efficiency, accuracy, and safety of pavement condition assessment and data collection. Drones, or unmanned aerial vehicles (UAVs), equipped with high-resolution cameras and other sensors can be used to collect aerial images and videos of pavements. This allows for rapid and comprehensive assessment of pavement distresses, such as cracking, rutting, and potholes, over large areas. Automated distress detection algorithms can be used to analyze the drone imagery and automatically identify and quantify pavement distresses. This reduces the need for manual inspections and improves the consistency and accuracy of the data. Sensors embedded in the pavement can provide continuous monitoring of pavement condition, including temperature, strain, and moisture content. This data can be used to track pavement performance over time and identify areas that are deteriorating rapidly. Mobile data collection systems, equipped with cameras, lasers, and GPS, can be used to collect pavement condition data at highway speeds. These systems can capture high-resolution images of the pavement surface, measure pavement roughness, and identify pavement distresses. LiDAR (Light Detection and Ranging) technology can be used to create three-dimensional models of pavements, providing detailed information about pavement surface texture and geometry. Ground-penetrating radar (GPR) can be used to assess the subsurface condition of pavements, including layer thickness, moisture content, and the presence of voids. Artificial intelligence (AI) and machine learning (ML) can be used to analyze large datasets of pavement condition data and predict future pavement performance. This allows agencies to make more informed decisions about pavement maintenance and rehabilitation. The use of these technologies can reduce the cost and time required for pavement condition assessment, improve the accuracy and consistency of the data, and enhance the safety of data collection operations. They enable agencies to proactively manage their pavement assets and make data-driven decisions about maintenance and rehabilitation.