Methodology for Analysis, Modeling and Simulation of Airport Gate-waiting Delays

Abstract

This dissertation presents methodologies to estimate gate-waiting delays from historical data, to identify gate-waiting-delay functional causes in major U.S. airports, and to evaluate the impact of gate operation disruptions and mitigation strategies on gate-waiting delay. Airport gates are a resource of congestion in the air transportation system. When an arriving flight cannot pull into its gate, the delay it experiences is called gate-waiting delay. Some possible reasons for gate-waiting delay are: the gate is occupied, gate staff or equipment is unavailable, the weather prevents the use of the gate (e.g. lightning), or the airline has a preferred gate assignment. Gate-waiting delays potentially stay with the aircraft throughout the day (unless they are absorbed), adding costs to passengers and the airlines. As the volume of flights increases, ensuring that airport gates do not become a choke point of the system is critical. The first part of the dissertation presents a methodology for estimating gate-waiting delays based on historical, publicly available sources. Analysis of gate-waiting delays at major U.S. airports in the summer of 2007 identifies the following. (i) Gate-waiting delay is not a significant problem on majority of days; however, the worst delay days (e.g. 4% of the days at LGA) are extreme outliers. (ii) The Atlanta International Airport (ATL), the John F. Kennedy International Airport (JFK), the Dallas/Fort Worth International Airport (DFW) and the Philadelphia International Airport (PHL) experience the highest gate-waiting delays among major U.S. airports. (iii) There is a significant gate-waitingdelay difference between airlines due to a disproportional gate allocation. (iv) Gate-waiting delay is sensitive to time of a day and schedule peaks. According to basic principles of queueing theory, gate-waiting delay can be attributed to over-scheduling, higher-than-scheduled arrival rate, longer-than-scheduled gate-occupancy time, and reduced gate availability. Analysis of the worst days at six major airports in the summer of 2007 indicates that major gate-waiting delays are primarily due to operational disruptions — specifically, extended gate occupancy time, reduced gate availability and higher-than-scheduled arrival rate (usually due to arrival delay). Major gate-waiting delays are not a result of over-scheduling. The second part of this dissertation presents a simulation model to evaluate the impact of gate operational disruptions and gate-waiting-delay mitigation strategies, including building new gates, implementing common gates, using overnight off-gate parking and adopting selfdocking gates. Simulation results show the following effects of disruptions: (i) The impact of arrival delay in a time window (e.g. 7 pm to 9 pm) on gate-waiting delay is bounded. (ii) The impact of longer-than-scheduled gate-occupancy times in a time window on gate-waiting delay can be unbounded and gate-waiting delay can increase linearly as the disruption level increases. (iii) Small reductions in gate availability have a small impact on gate-waiting delay due to slack gate capacity, while larger reductions have a non-linear impact as slack gate capacity is used up. Simulation results show the following effects of mitigation strategies: (i) Implementing common gates is an effective mitigation strategy, especially for airports with a flight schedule not dominated by one carrier, such as LGA. (ii) The overnight off-gate rule is effective in mitigating gate-waiting delay for flights stranded overnight following departure cancellations. This is especially true at airports where the gate utilization is at maximum overnight, such as LGA and DFW. The overnight off-gate rule can also be very effective to mitigate gate-waiting delay due to operational disruptions in evenings. (iii) Self-docking gates are effective in mitigating gate-waiting delay due to reduced gate availability.