Recommendations for NextGen Airport Surface Traffic Scheduling Algorithms: A Fast-time Simulation-based Perspective

Abstract

NASA researchers are developing surface optimization algorithms and a concept of operations for an airport surface traffic management tool called Spot And Runway Departure Advisor (SARDA). As part of this research, the SARDA scheduling algorithms have been adapted to work at several capacity-constrained airports. Adapting the SARDA scheduling algorithms to airports with dissimilar geometries and operational characteristics requires a careful study of the trade-offs between competing optimization objectives and conflicting constraints. This paper presents three trade-off studies, which were performed using a fast-time simulation of the Charlotte Douglas International airport (CLT). The first study explores a trade-off between minimizing system-wide delay and allocating delay equitably among flights. The equitable delay allocation objective was achieved through a simple scheduler formulation modification. The second study focuses on a tradeoff between minimizing system-wide delay and employing an aggressive gate holding strategy. The scheduler’s gate holding strategy was managed by adding a new departure queue duration scheduling parameter to control how long departures are allowed to wait in the runway queue. The third study explores the effectiveness of controlling how aircraft merge together in the ramp area in order to achieve a departure sequence which maximizes throughput. This study was motivated by CLT’s distinctive airport geometry, which forces departures to merge together in the ramp area to form departure sequences prior to reaching the runway. The paper describes and summarizes the results of these three studies.