The National Aeronautics and Space Administration (NASA) is developing automation for managing flight traffic on the airport surface to reduce taxi times and increase traffic throughput, without compromising safety. The scheduler is the part of the automation that calculates the advisories that assist the controller with clearing, holding, and sequencing flights. The Surface Operations Simulator and Scheduler (SOSS) is a fast-time airport surface operations simulator that connects to schedulers. SOSS is used to develop and test schedulers to determine if they can produce benefits. To show that schedulers developed with SOSS are credible, a validation of SOSS was performed to demonstrate that it is an accurate model of real operations. Surveillance and Federal Aviation Administration (FAA) operational performance data recorded from real operations at Charlotte Douglas International Airport were used to build a SOSS traffic scenario. The traffic scenario was run through SOSS to create simulated flight tracks. The flight tracks were analyzed to generate simulated taxi time and runway throughput metrics. Actual taxi time and runway throughput metrics were generated from the surveillance and FAA operational performance data. The simulated and actual metrics were compared. After the initial simulation, the average difference between simulated and actual taxi times on a flight by flight basis was not zero. A model tuning was performed by running the SOSS simulation multiple times while varying SOSS parameters to drive the average difference between the simulated and actual taxi times to zero. The SOSS parameters used were the pushback duration times and the taxi and ramp target speeds. Results show that the average difference between the simulated and actual taxi times was driven to zero. In addition, the standard deviations of the simulated taxi times and the actual taxi times were almost the same. However, the standard deviation of the flight by flight taxi time differences was large. This is because SOSS cannot simulate on an individual flight basis the exact actions taken by each flight in reality, which is an issue for all simulators. Despite this issue, SOSS was found to be a statistically accurate simulation of real airport operations, and schedulers developed and tested using SOSS have potential for producing benefits in real airport traffic management automation systems. NomenclatureASQP = Airline Service Quality Performance ASDE-X = Airport Surface Detection Equipment, Model X 1 Aerospace Engineer, Aerospace High Density Operations Branch, Mail Stop 210-15, Senior member. 2 ATCT = Air Traffic Control Tower CAI = Common Algorithm Interface CLT = airport code for Charlotte Douglas International Airport FAA = Federal Aviation Administration NASA = National Aeronautics and Space Administration SOSS = Surface Operations Simulator and Scheduler I. IntroductionASA is researching and developing automation that provides advisories to ramp, ground, and local controllers, who manage air traffic on the airport surface. 1 ...

Using a fast-time simulation tool Surface Operations Simulator and Scheduler, three gate pushback metering concepts are tested on a mock-up at Charlotte Douglas International Airport. The three concepts include (1) a mixed-integer-linear program to minimize aircraft delay, (2) a heuristic scheduler which uses aggregate aircraft counts to meter traffic, and (3) a first-come-first-served method that releases aircraft as soon as they are ready. A realistic scenario is created using surveillance data. By perturbing departure pushback times and arrival on-times, approximately 500 new scenarios are created from the original scenario. Additionally, pushback duration uncertainty and the inclusion of a miles-in-trail restriction are tested as independent variables. Results show that the calibration of certain model parameters on the mixed-integer-linear-program and heuristic scheduler strongly affect aircraft taxi times and delays. Also, the mixed-integer-linear-program is more robust to pushback duration uncertainties when there is a miles-in-trail restriction present.

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