SIMULATION ANALYSIS OF IMPLEMENTING END-AROUND TAXIWAY ON CROSSING RUNWAYS

At airports, aircraft taxi time may have effect on congestion, engine pollutants, and aircraft fuel consumption. An End-Around Taxiway (EAT) improves airport runway efficiencies and safety by providing a path for aircraft to move from one side of the runway to the other side without crossing that runway (FAA, 2022). The EAT has been implemented in four airports in the U.S.: Dallas/Fort Worth International Airport (KDFW), Hartsfield-Jackson International Airport (KATL), Detroit Metro Airport (KDTW), and Miami International Airport (KMIA) (Le, 2014). Currently, all the EATs are implemented at parallel runways. Previous research have shown that EAT on parallel runways has the potential to improve airport capacity and reduce fuel consumption (Fala et al., 2014; Feng & Johnson, 2021). There was no published application or research found about implementing EAT on crossing runways. This research is an explanatory study that focuses on analyzing the effect of EATs on airports with crossing runways. This research uses dynamic discrete event stochastic simulation software to build simulation models to analyze the effects of implementing EAT at crossing runways. Using a fictional airport loosely based on existing commercial service airports, the effect of EATs on a crossing runway airport was studied. The research has three experiments to measure the effects of the EAT in terms of taxi-in time, taxi-out time, and number of operations completed.

The major findings of the research are: 1) using EAT for taxi-in operations significantly reduces the taxi-in time and taxi-out time at the fictional airport with crossing runways; 2) using EAT for taxi-out operation significantly increases taxi-in time at the fictional airport with crossing runways; 3) using EAT for taxi-out operations significantly reduces taxi-out times at the fictional airport with crossing runways; 4) there is no statistical significance found when implementing EAT at the fictional airport with crossing runways in terms of number of operations completed per day. The configuration of the airport, the number of operations, the weather, and other factors may affect the transfer of these results to other airports with crossing runways.

Current EATs are only implemented and proposed at parallel runway airports. As aviation demand grows, this research may provide insights about a novel usage and operation strategy of EATs. The simulation model in this research is subject to assumptions and limitations. Future research is needed to improve the simulation model and further explore the effect of EATs on crossing runways.