Digital Twinning Approach for Transportation Infrastructure Asset Management Using UAV Data

Periodically monitoring, maintaining, and managing infrastructure assets are one of the key challenges faced by transportation agencies around the world. As per regulations, inspectors need to perform these tasks often to ensure optimum performance of the infrastructure with low life cycle costs. During the inspections, either the traffic operations are interrupted or the inspector can only get partial access to the infrastructure elements under inspection. These inspections include collecting data in different formats like notes, forms, and photos, and most of the time depends on the experience of the inspector, therefore, are subjective. Stationary and mobile laser-based instruments, which are expensive, are being used to scan the area, and these results upon analysis can provide an objective evaluation of the asset condition. However, there is a need to identify an effective data collection tool that is economical and can access hard-to-reach areas. The advent of unmanned aerial vehicle (UAV) platforms coupled with photogrammetry technologies has provided a solution to create a digital twin of the infrastructure asset and monitor its condition with minimum human interactions. The digital twin is a model-centric environment that offers a holistic view of real-field conditions of the infrastructure in a virtual environment facilitating effective information sharing and analysis. This study presents two case studies where a UAV mounted with a visible camera was used to create digital twins of different phases of infrastructure for better monitoring and management of transportation assets. This study provides an approach that can benefit transportation agencies in conducting preventive rather than reactive maintenance works, which can result in significant cost savings.