Decision making in an airport environment is often complex and time-consuming. Many decisions involve numerous stakeholders and considerable resources and can include an element of unanticipated adverse impacts if a less-than-optimal decision is made. “Digital twins” are detailed virtual representations of a facility or system that are kept up-to-date with real-time data. The most advanced examples are supported by machine learning and reasoning. Digital twins allow for speedier and more confident decision making, enabling not only a better understanding of how a system operates but also how a system might operate under different parameters. Although initially limited to the domain of manufacturers and engineers, digital twins are being employed in an ever-widening array of settings. Since airports often consist of a complex set of interactive systems, the potential value of digital twins for airports could be significant. Yet the development, operation, and maintenance of a digitial twin will require a significant investment of resources, and research is needed to help airports understand the potential benefits of digital twins and the steps for implementing and maintaining a digital twin for their airport.
The objective of this research is to develop guidance and tools for airports to evaluate the potential benefits that a digital twin might provide for decision making, identify which aspects of the airport could be included, and develop a digital twin that is scalable to their unique needs.