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NASA NTRS2014

Overview: Spot and Runway Departure Advisor (SARDA)

Spot and Runway Departure Advisor (SARDA) is a decision support tool to assist airline ramp controllers and ATC tower controllers to manage traffic on the airport surface to significantly improve efficiency and predictability in surface operations. The core function of the tool is the runway scheduler which generates an optimal solution for runway sequence and schedule of departure aircraft, which would minimize system delay and maximize runway throughput. The presentation describes the concept of the SARDA tool and results from human-in-the-loop simulations conducted in 2012 for DallasFt. Worth International Airport. The presentation also explains the latest status of NASA's current surface research through a collaboration with an airline partner. The presentation concludes with a discussion on other on-going as well as future surface research.

decision support tool↗
NASA NTRS2019

Airspace Technology Demonstration 2 (ATD-2) Phase 2 Technology Description Document (TDD)

This Technology Description Document (TDD) provides an overview of the technology for the Phase 1 Baseline and Phase 2 Fused demonstrations of the Integrated Arrival, Departure, and Surface (IADS) prototype system of the National Aeronautics and Space Administration’s (NASA) Airspace Technology Demonstration 2 (ATD-2) project, which has been demonstrated since October of 2017 at Charlotte Douglas International Airport (CLT). Development, integration, and field demonstration of relevant technologies of the IADS system directly address recommendations made by the Next Generation Air Transportation System (NextGen) Integration Working Group (NIWG) on Surface and Data Sharing and the Surface Collaborative Decision Making (Surface CDM) concept of operations developed jointly by the Federal Aviation Administration (FAA) and aviation industry partners. NASA has been developing the IADS traffic management system under the ATD-2 project in coordination with the FAA, flight operators, CLT airport operators, and the National Air Traffic Controllers Association (NATCA). The primary goal of ATD-2 is to improve the predictability and operational efficiency of the air traffic system in metroplex environments, through the enhancement, development, and integration of the nation’s most advanced and sophisticated arrival, departure, and surface prediction, scheduling, and management systems. The ATD-2 project is a 5-year research activity beginning in 2015 and extending through 2020. The Phase 1 Baseline IADS capability resulting from the ATD-2 research has been demonstrated at the CLT airport since the beginning of October 2017. Phase 1 provided data exchange and integration with the initial demonstration of the integrated system of strategic and tactical scheduling, collaborative tactical surface metering, tactical departure scheduling to an en route meter point and overhead stream insertion, initial integration of a TFDM SWIM prototype feed, and an early implementation prototype of a Terminal Flight Data Manager (TFDM) Electronic Flight Data (EFD) system. The strategic surface scheduling element of the capability is consistent with the Surface CDM Concept of Operations published in 2014 by the FAA Surface Operations Directorate.1 The Phase 2 Fused IADS system provided substantial updates to baseline IADS Demonstration capability. Improvements were made to the IADS modeler; tactical surface scheduling, and metering; tactical departure scheduling for overhead stream insertion; Electronic Flight Data (EFD) and the integration with the FAA Advanced Electronic Flight Strip (AEFS); RTC/RMTC, and departure trajectories. New capabilities included a TFDM SWIM prototype feed and delivery of IADS data via the TFDM Terminal Publication (TTP) service of the FAA’s SWIM system; strategic surface scheduling and metering as well as fusion with tactical surface metering; integration and ingestion of data from TTP-connected Mobile App and texting industry for General Aviation (GA) flights; and expansion of airspace deployments to include adjacent Center automation, in particular interface with the Atlanta Center (ZTL) arrival metering TBFM system to evaluate pre-scheduling of flights. Improvements in Data Analysis and System Health (DASH) monitoring and updates were completed as well.

Talebi, Ehsan↗
NASA NTRS2015

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

Accurate taxi time prediction can be used for more efficient runway scheduling to increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. This paper describes two different approaches to predicting taxi times, which are a data-driven analytical method using machine learning techniques and a fast-time simulation-based approach. These two taxi time prediction methods are applied to realistic flight data at Charlotte Douglas International Airport (CLT) and assessed with actual taxi time data from the human-in-the-loop simulation for CLT airport operations using various performance measurement metrics. Based on the preliminary results, we discuss how the taxi time prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast-time simulation model for implementing it with an airport scheduling algorithm in real-time operational environment.

Lee, Hanbong↗
NASA NTRS2018

Airspace Technology Demonstration 2 (ATD-2) Technology Description Document (TDD)

This Technology Description Document (TDD) provides an overview of the technology for the Phase 1 Baseline Integrated Arrival, Departure, and Surface (IADS) prototype system of the National Aeronautics and Space Administration's (NASA) Airspace Technology Demonstration 2 (ATD-2) project, to be demonstrated beginning in 2017 at Charlotte Douglas International Airport (CLT). Development, integration, and field demonstration of relevant technologies of the IADS system directly address recommendations made by the Next Generation Air Transportation System (NextGen) Integration Working Group (NIWG) on Surface and Data Sharing and the Surface Collaborative Decision Making (Surface CDM) concept of operations developed jointly by the Federal Aviation Administration (FAA) and aviation industry partners. NASA is developing the IADS traffic management system under the ATD-2 project in coordination with the FAA, flight operators, CLT airport, and the National Air Traffic Controllers Association (NATCA). The primary goal of ATD-2 is to improve the predictability and operational efficiency of the air traffic system in metroplex environments, through the enhancement, development, and integration of the nation's most advanced and sophisticated arrival, departure, and surface prediction, scheduling, and management systems. The ATD-2 project is a 5-year research activity beginning in 2015 and extending through 2020. The Phase 1 Baseline IADS capability resulting from the ATD-2 research will be demonstrated at the CLT airport beginning in 2017. Phase 1 will provide the initial demonstration of the integrated system with strategic and tactical scheduling, tactical departure scheduling to an en route meter point, and an early implementation prototype of a Terminal Flight Data Manager (TFDM) Electronic Flight Data (EFD) system. The strategic surface scheduling element of the capability is consistent with the Surface CDM Concept of Operations published in 2014 by the FAA Surface Operations Directorate.

integrated arrival↗
NASA NTRS2020

ATD-2 Phase 3 Scheduling in a Metroplex Environment Incorporating Trajectory Option Sets

The NASA Airspace Technology Demonstration 2 Phase 1 and 2 Field Evaluations have successfully demonstrated new technologies developed to manage the Integrated Arrival, Departure, and Surface traffic flows at a single airport. The Phase 3 Field Evaluation extends the capabilities to a Metroplex environment where multiple airports are interacting and sharing resources along the terminal boundary. This paper describes the scheduling algorithm enabling the coordinated scheduling and describes the interaction between airports within the Metroplex and the terminal boundary. We describe the metrics developed to inform flight operators about reroute opportunities and discuss the potential benefits to the rerouted flight and the system-wide aggregate benefits of a single reroute. We believe that the capabilities developed and the lessons learned during the Phase 3 Field Evaluation will set up the National Airspace System for future success.

Airspace Technology Demonstration 2↗
NASA NTRS2016

SARDA Surface Schedulers

Provide an overview of algorithms used in SARDA (Spot and Runway Departure Advisor) HITL (Human-in-the-Loop) simulation for Dallas Fort-Worth International Airport and Charlotte Douglas International airport. Outline a multi-objective dynamic programming (DP) based algorithm that finds the exact solution to the single runway scheduling (SRS) problem, and discuss heuristics to restrict the search space for the DP based algorithm and provide improvements.

runways scheduling↗
NASA NTRS2018

Performance Evaluation of Conflict-Free Trajectory Taxiing in Airport Ramp Area Using Fast-Time Simulations

The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been collaborating to conduct joint research addressing future surface traffic management challenges. The surface management tool from DLR, called Taxi Routing for Aircraft: Creation and Controlling (TRACC), was adapted to be integrated in NASA's fast-time simulation environment called Surface Operations Simulator and Scheduler (SOSS). The research described in this paper 1) applied TRACC to trajectory-based ramp traffic management, where TRACC generates conflict-free aircraft trajectories in a congested ramp area, 2) investigated the feasibility of the concept through the integrated TRACC-SOSS fast-time simulation, and 3) evaluated the performance of the integrated system. For this activity, TRACC was adapted for ramp operations at Charlotte Douglas International Airport, called TRACC_PB (TRACC for pushback optimization). TRACC_PB provides four-dimensional taxi trajectories with a command speed profile for each aircraft following standard taxi routes within the ramp area. In this study, departures are given the Target Movement Area entry Times (TMATs) provided by the baseline surface metering scheduler based on NASA's Spot and Runway Departure Advisor (SARDA). TRACC_PB also calculates optimal pushback times for departures, as well as the times when arrivals shall enter the ramp, the Target Movement area Exit Times (TMETs). The initial results showed that the TRACC_PB successfully generated conflict-free trajectories for the ramp area taxi operations and improved taxiing efficiency compared to the baseline results. TRACC_PB aimed to provide conflict-free taxi routes avoiding any stops while taxiing. This resulted in longer gate hold times for departures and postponed throughput values compared to the baseline simulation without trajectory optimization. Having conflict-free routes without stoppage also created shorter taxi times but required renegotiation of the given TMATs. TRACC_PB also achieved reductions in both fuel consumption and engine emissions (17% for departures and 10% for arrivals), which correlate with the ramp taxi time reduction.

trajectory-based taxi operations↗
NASA NTRSDate not supplied

Impact of General Aviation Operations on Airport Performance Through Fast-Time Simulations at Charlotte Douglas International Airport

NASA, in partnership with the Federal Aviation Administration and commercial airlines, deployed the Integrated Arrival, Departure, and Surface (IADS) traffic management system at Charlotte Douglas International Airport (CLT) in 2017 for field evaluation. The system features new capabilities of data exchange and integration, collaborative surface metering and scheduling, which has demonstrated operational benefits of reducing delay time and fuel consumption. General Aviation flights, however, are not currently included in the surface metering programs because of their different operational procedures and lack of reliable predictability in departure time. Thus, their impact on the system performance is not well understood. This paper presents a study of the impact of General Aviation traffic at CLT using fast-time simulations.

General Aviation↗
NASA NTRS2014

A Concept of Operations for Far-Term Surface Trajectory-Based Operations (STBO)

The goal of this far-term STBO (Surface Trajectory-Based Operations) ConOps (Concept of Operations) is to increase the efficiency and predictability of airport surface operations, and reduce the environmental impact, by incorporating a time-based component to surface operations. In the far-term NextGen timeframe, airport surface operations will transition from current-day first-come, first-served operations, to strategically scheduled operations in which pilots are recruited as active participants in meeting the precise time-based goals of NextGen surface operations. The far-term STBO concept includes two-phases. Phase 1 introduces time-based traffic flow constraint points, which divide the taxi route into segments with an assigned Required Time of Arrival (RTA). This Phase 1 approach provides temporal certainty only near the traffic flow constraint points, but not in between. Minimal augmentations to the flight deck are required to support required time of arrival (RTA) management. Phase 2 further increases precision and efficiency by introducing full four-dimensional (4D) trajectories, with an x-y location for all times t. This phase assumes adoption of advanced flight deck equipage enabling higher temporal precision sufficient to support aircraft conformance to 4D trajectories. This allows more precision and less temporal uncertainty at all times along the route.

Surface Trajectory-Based Operations (STBO)↗
NASA NTRS2017

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

A real time dashboard was developed in order to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users across a number of roles benefit from a real time system that enables common situational awareness. In addition to shared situational awareness the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial set of metrics computed on operational data. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017; Charlotte-Douglas International Airport. Analysis and metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of metrics across delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

integrated arrival departure surface operations↗
NASA NTRS2019

Scheduling Improvements Following the Phase 1 Field Evaluation of the ATD-2 Integrated Arrival, Departure, and Surface Concept

NASA is conducting the Airspace Technology Demonstration-2 to evaluate an Integrated Arrival, Departure, and Surface (IADS) traffic management system that extends traffic sequencing for the entire life-cycle of a flight from departure gate to arrival gate within multi-airport, metroplex environments. After development and testing in human-in-the-loop simulations, the IADS system was deployed to Charlotte Douglas International Airport for a three-year field evaluation. From the initial IADS concept development through the end of the Phase 1 field evaluation many lessons were learned with regards to the IADS scheduler. In this paper we describe how data from the Phase 1 field evaluation helped identify scheduler improvements and guided the implementation of refinements. The improvements in the IADS scheduler described in this paper are incorporated into the IADS Phase 2 scheduler enabling strategic Surface Metering Programs and will be evaluated during the field evaluation.

Coupe, William J.↗
NASA NTRS2019

Scheduling Improvements Following the Phase 1 Field Evaluation of the ATD-2 Integrated Arrival, Departure, and Surface Concept

NASA is conducting the Airspace Technology Demonstration-2 (ATD-2) to evaluate an Integrated Arrival, Departure, and Surface (IADS) traffic management system that extends traffic sequencing for the entire life-cycle of a flight from departure gate to arrival gate within multi-airport, metroplex environments. After development and testing in human-in-the-loop simulations, the IADS system was deployed to Charlotte Douglas International Airport for a three-year field evaluation. From the initial IADS concept development through the end of the Phase 1 field evaluation many lessons were learned with regards to the IADS scheduler. In this paper we describe how data from the Phase 1 field evaluation helped identify scheduler improvements and guided the implementation of refinements. The improvements in the IADS scheduler described in this paper are incorporated into the IADS Phase 2 scheduler enabling strategic Surface Metering Programs and will be evaluated during the field evaluation.

Airspace Technology Demonstration-2↗
NASA NTRS2003

Runway Operations Planning: A Two-Stage Solution Methodology

The airport runway is a scarce resource that must be shared by different runway operations (arrivals, departures and runway crossings). Given the possible sequences of runway events, careful Runway Operations Planning (ROP) is required if runway utilization is to be maximized. Thus, Runway Operations Planning (ROP) is a critical component of airport operations planning in general and surface operations planning in particular. From the perspective of departures, ROP solutions are aircraft departure schedules developed by optimally allocating runway time for departures given the time required for arrivals and crossings. In addition to the obvious objective of maximizing throughput, other objectives, such as guaranteeing fairness and minimizing environmental impact, may be incorporated into the ROP solution subject to constraints introduced by Air Traffic Control (ATC) procedures. Generating optimal runway operations plans was approached in with a 'one-stage' optimization routine that considered all the desired objectives and constraints, and the characteristics of each aircraft (weight class, destination, Air Traffic Control (ATC) constraints) at the same time. Since, however, at any given point in time, there is less uncertainty in the predicted demand for departure resources in terms of weight class than in terms of specific aircraft, the ROP problem can be parsed into two stages. In the context of the Departure Planner (OP) research project, this paper introduces Runway Operations Planning (ROP) as part of the wider Surface Operations Optimization (SOO) and describes a proposed 'two stage' heuristic algorithm for solving the Runway Operations Planning (ROP) problem. Focus is specifically given on including runway crossings in the planning process of runway operations. In the first stage, sequences of departure class slots and runwy crossings slots are generated and ranked based on departure runway throughput under stochastic conditions. In the second stage, the departure class slots are populated with specific flights from the pool of available aircraft, by solving an integer program. Preliminary results from the algorithm implementation on real-world traffic data are included.

Anagnostakis, Ioannis↗
NASA NTRS2011

Precision Departure Release Capability (PDRC) Integration, Evaluation and Transition

NASA's Precision Departure Release Capability (PDRC) research activity is assessing the use of surface trajectory-based takeoff (OFF) time estimates for en route domain departure scheduling in Call For Release situations. Current aircraft departure release times computed by an Air Traffic Management decision support tool to meet Call For Release constraints are based on coarse estimates of aircraft OFF times. Uncertainty in OFF time estimates may result in missed opportunities to merge into an overhead stream and lost throughput. However, technology exists to improve OFF time estimates by using more accurate aircraft trajectory predictions available in NextGen airport surface management decision support tools. PDRC findings are expected to be broadly applicable to NextGen integrated arrival/departure/surface implementations. For concept development and evaluation purposes this research activity integrates NASA's Surface Management System (SMS) OFF time prediction capabilities with Traffic Management Advisor (TMA) departure scheduling functions. PDRC field evaluations are being conducted at the North Texas (NTX) Research Station. The NASA/FAA Integrated Arrival/Departure/Surface Research Transition Team is using PDRC as a pathfinder for developing technology transfer mechanisms and procedures.

Engelland, Shawn A.↗
NASA NTRSDate not supplied

Human Factors Impact of Different Ramp Controller Scheduling Advisories for ATD-2 Surface Metering in a Human-in-the-Loop Simulation

A human-in-the-loop (HITL) simulation took place in 2019 at NASA Ames Research Center’s Future Flight Central, an airport simulator with a full-scale 360-degree view that showed real-time airport operations at Dallas/Fort Worth International Airport (DFW). The HITL was part of the NASA/FAA Airspace Technology Demonstration 2 (ATD-2) project which involves an on-going field demonstration at Charlotte Douglas International Airport (CLT). In the field demonstration, metering on the airport surface takes place with one of the goals being to reduce runway queue length by holding aircraft at the gate during busy times, thereby reducing fuel burn and CO2 emissions. This goal has been successfully accomplished at CLT by showing Ramp Controllers when to release aircraft at the gate so as to reduce aircraft waiting in the queue. Among the questions that the current simulation at DFW was designed to address were, "Which types of advisories to the Ramp Controllers work best, those that show a ±2 minute window for a release time from the gate, or a ±5 minute window for an arrival time at the spot (where Air Traffic Control takes over) or both?" and "How do these different types of advisories affect Ramp Controller workload and situation awareness?" Another question was, “Does a ramp that is less restrictive than the one at CLT affect compliance with these advisories?”

Bonny K Parke↗
NASA NTRS2017

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

To address the Integrated Arrival, Departure, and Surface (IADS) challenge, NASA is developing and demonstrating trajectory-based departure automation under a collaborative effort with the FAA and industry known Airspace Technology Demonstration 2 (ATD-2). ATD-2 builds upon and integrates previous NASA research capabilities that include the Spot and Runway Departure Advisor (SARDA), the Precision Departure Release Capability (PDRC), and the Terminal Sequencing and Spacing (TSAS) capability. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users of the tools across a number of roles benefit from a real time system that enables common situational awareness. A real time dashboard was developed to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. In addition to shared situational awareness, the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial proposed set of metrics. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport (CLT). The architecture of implementing such a tool as well as potential uses are presented for operations at CLT. Metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of system delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform users of the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

integrated arrival departure surface operations↗
NASA NTRS2017

Optimization of Airport Surface Traffic: A Case-Study of Incheon International Airport

This study aims to develop a controllers' decision support tool for departure and surface management of ICN. Airport surface traffic optimization for Incheon International Airport (ICN) in South Korea was studied based on the operational characteristics of ICN and airspace of Korea. For surface traffic optimization, a multiple runway scheduling problem and a taxi scheduling problem were formulated into two Mixed Integer Linear Programming (MILP) optimization models. The Miles-In-Trail (MIT) separation constraint at the departure fix shared by the departure flights from multiple runways and the runway crossing constraints due to the taxi route configuration specific to ICN were incorporated into the runway scheduling and taxiway scheduling problems, respectively. Since the MILP-based optimization model for the multiple runway scheduling problem may be computationally intensive, computation times and delay costs of different solving methods were compared for a practical implementation. This research was a collaboration between Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA).

surface management↗
NASA NTRS2017

Optimization of Airport Surface Traffic: A Case-Study of Incheon International Airport

This study aims to develop a controllers decision support tool for departure and surface management of ICN. Airport surface traffic optimization for Incheon International Airport (ICN) in South Korea was studied based on the operational characteristics of ICN and airspace of Korea. For surface traffic optimization, a multiple runway scheduling problem and a taxi scheduling problem were formulated into two Mixed Integer Linear Programming (MILP) optimization models. The Miles-In-Trail (MIT) separation constraint at the departure fix shared by the departure flights from multiple runways and the runway crossing constraints due to the taxi route configuration specific to ICN were incorporated into the runway scheduling and taxiway scheduling problems, respectively. Since the MILP-based optimization model for the multiple runway scheduling problem may be computationally intensive, computation times and delay costs of different solving methods were compared for a practical implementation. This research was a collaboration between Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA).

taxi scheduler↗