Explainable Algorithm to Predict Passenger Flow at Cincinnati/Northern Kentucky International Airport

Abstract

We present an algorithm for the prediction of the incoming passengers at the airport’s security checkpoint with a resolution of 15 min for 2 weeks following the day of the prediction. This is characterized not only for its performance but also from its explainability in the outcomes. The algorithm has been integrated successfully at Cincinnati/Northern Kentucky International Airport (CVG) for daily passenger predictions, which ultimately equipped the airport managers with information to perform a data-driven deployment of the necessary airport resources. These range from tailored Transportation Security Administration (TSA) officer schedules and staff allocation to surveillance and supervision tasks. Some of the indirect consequences of this technology are congestion avoidance, the improvement of overall security at the airport facilities, the reduction of the waiting times, and the enhancement of the passenger experience.