We model the impact of weather and arrival demand on ground delay program (GDP)
incidence. We use Support Vector Machine (SVM) to analyze how regional convective …

Autonomous Vehicle (AV) technology is a disruptive transportation technology that promises
to revolutionize how people travel. Due to their potential mobility benefits and associated …

Aircraft recovery, a critical step in airline operations recovery, aims to minimize the cost of
disrupted aircraft schedules. The exact methods for aircraft recovery are computationally …

The field of aviation research is entering the era of big data. While data-driven
advancements in aviation have clearly brought about applicable models and results with …

The slot allocation mechanism aims to match flight demand and airport resources from a
strategic perspective. However, current research mainly focused on airlines' interests …

We address an airline-driven flight rescheduling problem within a single airport in which a
series of ground delay programs (GDPs) are considered. The objective of the problem is to …

Abstract Air Traffic Flow Management (ATFM) is the backbone of modern aviation and
ensures that aircraft move safely and efficiently through increasingly congested skies. As …

Abstract Efficient planning of Airport Acceptance Rates (AARs) is key for the overall
efficiency of Traffic Management Initiatives such as Ground Delay Programs (GDPs). Yet …

Traffic flow prediction is a significant component for the new generation intelligent
transportation. In the field of air transportation, accurate prediction of airport flight flow can …

Effective ground delay programs (GDP) are needed to intervene when there are bad
weather or airport capacity issues. This paper proposes a new methodology for predicting …