Simulating airline operational responses to airport capacity constraints

Abstract

Between 1960 and 2011, worldwide scheduled passenger air travel grew by more than 7% per year. Most projections suggest that the demand for air travel will continue to increase strongly, by around 5% per year over the coming decades. This strong anticipated growth, however, does not account for any air transport infrastructure constraints. Airport and airspace capacity may not be expanded at a rate sufficiently high to enable the projected demand growth, which may lead to lower than anticipated growth in aviation. This paper describes and applies a recently developed model that predicts airline operational responses to airport capacity constraints. It does this by simulating a Nash best-response game between competing airlines, in which each airline maximizes its profit by adjusting flight frequencies and passenger routing, attempting to gain market share by increasing flight frequencies, but at the cost of the added flights. The model is validated for a network of airports in the United States in 2005 and applied to simulate airline operational changes through 2030 under two capacity-constrained scenarios: frozen 2005 capacity levels on (i) a system-wide scale, and (ii) only at Chicago O׳Hare International, a primary hub airport. Simulated passenger demand, air traffic, flight delays, system CO2 emissions and Chicago O׳Hare NOx emissions are compared to a case in which airport capacity is expanded according to existing airport expansion plans. The simulation results indicate that the air transport system would adjust operations within a constrained network in such way as to avoid airports with high delays. While most system-wide implications for operations and environmental impact seem to be manageable, local impacts at congested hub-airports may be significant.