Upper and Lower Bound Estimation of Runway Throughput in the Presence of Uncertainty

Abstract

Upper and lower bound estimation for runway capacity are presented in the presence of various uncertainties for a single runway airport. Currently, arrivals touch down on runways are either assumed to be predetermined and controllable, or fully controllable. Also, uncertainties in aircraft trajectories, whether they are on the ground or in the air, are dealt with reactively as opposed to proactively. As one of the solutions to these problems stated, a two stage stochastic model can be formulated to determine feasible and optimal schedule for both arrival and departure at runway, taxiway and ramp. In order to show the necessity of developing the stochastic model for optimizing arrival and departure schedule in feasible bound, several study cases are introduced along with the results using Monte-Carlo simulation for a single runway airport in this paper. In this study, both arrival and departure capacity are calculated for various service rates of runway for 1) predetermined/uncontrollable and 2) fully controllable arrival stream. Also, the case with and without uncertainty from arrival-departure interaction and taxi time distribution are included in Monte-Carlo simulation to study the effect of uncertainty. Although both arrival and departure capacity decrease with number of uncertainty added in the simulation, the average departure capacity increases by modifying the arrival stream from an non-integer to an integer problem while maintaining similar average arrival capacity, especially at busy hour of airport. This result shows the benefit of modifying the arrival stream as an integer problem for optimizing the runway resource as well as overall airport operation efficiency. Based on numerical results, predetermined/uncontrollable and controllable arrival stream are planned to be used for lower and upper bound estimation, respectively, in the presence of various uncertainty in two stage stochastic model in the future.