Endogenous control of service rates in stochastic and dynamic queuing models of airport congestion

• Integration of tactical operating procedures into a strategic model of congestion.
• Estimation of airport delays using a stochastic and dynamic queuing model.
• Formulation of an efficient control of arrival and departure service rates.
• The model estimates well the average and variability of delays at JFK, EWR and LGA.
• Large delay declines between 2007 and 2011 largely explained by small changes in demand.

Airport congestion mitigation requires reliable delay estimates. This paper presents an integrated model of airport congestion that combines a tactical model of capacity utilization into a strategic queuing model. The model quantifies the relationships between flight schedules, airport capacity and flight delays, while accounting for the way arrival and departure service rates can be controlled over the day to maximize operating efficiency. We show that the model estimates the average and variability of the delays observed at New York’s airports relatively well. Results suggest that delays can be extremely sensitive to even small changes in flight schedules or airport capacity.