Aditya Saraf

Validation of Simulations of Airport Surface Traffic with the Surface Operations Simulator and Scheduler

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.

Evaluating Concepts for Metroplex Operations

Metropolitan areas with high traffic demand are often served by a system of two or more airports whose arrival and departure operations are highly interdependent. Such an airport system is referred to as a metroplex. A temporal-spatial framework for evaluating concepts for improving metroplex operations was developed. In this framework, concepts for metroplex operations were defined by their spatial and temporal impacts on operations. These impacts were evaluated parametrically with a Generic Metroplex model. The experiment revealed that temporal scheduling and route segregation are the two most important integrated concepts for reducing delays in the terminal area airspace. These two concepts were then incorporated to form an experiment matrix, and their effects were tested in a metroplex model based on the New York terminal area airspace. Simulation analyses showed a nearly 80% reduction in queueing delay for arrival flights when the scheduling and route structural design were combined and more than 60% reduction with scheduling alone.

Super Density Operations Airspace Modeling for the Southern California Metroplex

This paper discusses the process for and results of developing a candidate airspace model that describes airport runway configurations, arrival and departure procedures and routes for airplanes arriving to and departing from the Southern California TRACON (SCT). The airspace model includes arrival and departure traffic routes for six major Southern California metroplex airports including Los Angeles International (LAX), Burbank (BUR), Ontario (ONT), Long Beach (LGB), Santa Ana (SNA), and San Diego (SAN). The model comprises a series of airspace model components including: a) the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM)-based characterization of the operating conditions of all six airports throughout 2009 and 2010; b) trajectory data-based modeling of arrival and departure traffic flow routes and altitude ranges and comparison against published Departure Procedures (DPs) and Standard Terminal Arrival Routes (STARs); c) route and airspace traffic volume analysis to identify the most commonly used arrival and departure procedures and to identify the fraction of total metroplex airspace traffic associated with each procedure; d) modeling and analysis of continuous descent and standard arrival procedures and departure procedures spanning the entire terminal airspace between the en-route airspace and the runway threshold of each airport; and e) trajectory generator-based evaluation of modeled procedures to ensure flyability of modeled procedures.

Metroplex Demand Analysis and Applications

,A metroplex is a group of two or more adjacent airports whose arrival and departure operations are highly interdependent. The NASA Airportal Project’s Characterization of and Concepts for Metroplex Operations study investigated current sources of metroplex inefficiency and evaluated methods for improving performance. Metroplex demand analysis supported the study by generating traffic demand schedules for the evaluation of four hypothetical metroplex configurations. Each generated traffic demand schedule was the adaptation of a real-world airport traffic demand schedule to a hypothetical metroplex airport according to the specified demand loading and airspace geometry. The generated traffic demand sets were applied in subsequent analyses of metroplex airspace geometry, scheduling, and metering precision. This paper discusses the metroplex demand analysis process, its application to the Characterization of and Concepts for Metroplex Operations study, and its application to metroplex demand redistribution impact evaluation.

Discussion and Comparison of Metroplex-wide Arrival Scheduling Algorithms

This paper discusses three candidate metroplex-wide arrival scheduling algorithms that are aimed at improving the efficiency of and the coordination between arrival operations in a metroplex environment. We present analysis results obtained by applying the candidate algorithms to a generic metroplex model. Four different metroplex-boundary fix configurations were studied in this process. However, in this paper, we elaborate differences between the algorithms and present a comparison of their performance as applied to one of these boundary fix configurations. Initial results show that scheduling strategies, which try to minimize the impact of upstream constraints on individual airport runway utilization while trying to optimize crossing sequences at all key upstream scheduling points and the runway at the same time, provide the most benefits in terms of minimizing delay and fuel cost impacts of metroplex interactions. I. Introduction Federal Aviation Administration (FAA), the Joint Planning and Development Office (JPDO) and others have projected a significantly increased demand over the timeframe of the Next Generation Air Transportation System (NextGen). It is expected that much of future National Airspace System (NAS) air traffic demand growth will be in major metropolitan areas. In today’s NAS, metropolitan areas with high demand are often served by a group of two or more airports whose arrival and departure operations are highly interdependent. Such a group is defined as a “metroplex” by the JPDO [JPDO]. The resulting traffic growth in metropolitan areas will increase the coupling of operations in the metroplexes that already exist, increase expected NAS delays, and will potentially create new metroplexes.

Benefits Assessment of a Surface Traffic Management Concept at a Capacity-Constrained Airport

Inefficient surface traffic management may lead to congested taxiways, long departure queues, and excess delay in the air transportation system. To address this problem, NASA researchers have developed optimization algorithms and a concept of operations for an airport surface traffic management tool called the Spot and Runway Departure Advisor (SARDA). Past SARDA research efforts have been focused on the Dallas/Fort Worth International airport. This paper describes the development of SARDA-like schedulers for managing the traffic at an operationally dissimilar airport―Charlotte Douglas International airport, and presents the results of a fast-time simulation-based benefits assessment. Fasttime simulations were conducted to test the benefits of optimized scheduling over a baseline model of current-day operations. In the fast-time simulations, it was observed that optimization schedulers reduced movement area delays by up to 3.1 minutes per departure on average, as compared to the baseline simulation. The movement area delay savings translated to shorter movement area taxi-out times and an average reduction in fuel burn and emissions of approximately 24% per departure. The overall trend observed in the total delay (gate delay + ramp delay + movement area delay) comparison indicated the optimization schedulers were not able to reduce total delay, and runway throughput comparisons suggested the optimization schedulers had little to no effect on throughput.

ACES terminal model enhancement

Terminal Model Enhancement is an advanced modeling capability for simulating terminal area airport and airspace traffic operations. But, more importantly, TME is a platform for testing advanced air traffic management concepts using plug-and-play modeling. TME augments the existing airport surface and terminal airspace modeling capabilities of NASAs Airspace Concept Evaluation System, an agent-based fast-time National Airspace System simulation. TME supports detailed analysis of concepts addressing future surface and terminal airspace operations. TME models 4-dimension trajectories and provides a system of pluggable components upon which replacement components can be developed to model alternative operational concepts. TME Airport ATC and TFM agents generate surface route plans, move aircraft through a vertex-edge graph, implementing pilot self-separation and controller conflict resolution, gridlock avoidance and gate utilization models. TME TRACON ATC, TFM and Flight agents apply advanced sequencing and spacing modeling to determine conflict-resolved airspace route plans, assign landing times and use 4D trajectory modeling to fly aircraft along route plans. TME introduces a unique runway operations model that integrates TRACON landing management with Airport ATC takeoff and runway taxi crossing management.

Analysis of Airport Surface Schedulers Using Fast-time Simulation

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.

Fast and Efficient Method for Generating Airport Models to Support National Airspace System Analyses

NASA NextGen-Airspace Project’s System Level Design, Analysis, and Simulation Tools (SLDAST) Research Focus Area (RFA) has developed the Airspace Concept Evaluation System (ACES) for the assessment of the impact of advanced Air Traffic Management (ATM) concepts. Currently, ACES does not have detailed airport surface models which are required for detailed assessment of NextGen surface ATM concepts. To bridge this gap, the SLDAST Airport Scenario Generation Team (ASGT), composed of NASA Ames Research Center, Perot Systems, Sensis Corporation, and Optimal Synthesis Inc., undertook an effort to generate detailed link-node models for airport surfaces and convert these airport linknode models into a format suitable for ACES. This paper outlines the SLDAST airport linknode model generation and conversion processes, and summarizes the use of these models to support ACES-based assessments. A companion paper will describe in detail the software tools (SurfTools) used in this airport model generation process.

Assessment of the Potential Benefits of an Ideal Integrated Metroplex-Wide Departure Planner

More efficient metroplex operations as a result of Next-Generation Air Transportation System (NextGen) Operational Improvements (OIs) is an important component of the Integrated Work Plan envisioned by the FAA’s Joint Planning and Development Office (JPDO). Non-real-time simulations can be used to estimate the benefits of advanced metroplex scheduling concepts such as those envisioned by the JPDO. NASA NextGenAirspace Project’s, System Level Design, Analysis, and Simulation Tools (SLDAST) Research Focus Area (RFA) has developed the Airspace Concept Evaluation System (ACES) for assessment of the impact of advanced Air Traffic Management (ATM) concepts. This paper describes the use of ACES Build 5.0 to perform a preliminary NextGen metroplex assessment study. The objective of this study was to investigate the potential benefits of a Multi-airport Departure Planner. The New York metroplex (N90) was the focus region for this assessment.