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NASA NTRS2021

Predicting Arrival and Departure Runway Assignments with Machine Learning

Runway assignments at major airports are made by air traffic controllers subject to various constraints, and to achieve various objectives. In this research, we describe our efforts training machine learning (ML) models to predict both departure and arrival runway assignments using an entirely data-driven approach. This approach is compared to existing rule-based approaches developed in previous research using input from Subject Matter Experts. The models have features derived from various FAA data feeds, and leverage multiple machine learning algorithms. Results for models trained for nine major U.S. airports are described and compared to one another across various important dimensions. Particular attention was paid to developing a repeatable framework for training these models so the approach could be scaled to other airports, and to developing models that are useful in a real-time environment. In addition, the models were designed to be functional in a real-time environment to support NASA’s ATD-2 project, as part of an ML-powered shadow system to compare against the performance of the fielded system.

machine learning↗

NASA NTRS2021

Predicting Arrival and Departure Runway Assignments with Machine Learning

machine learning↗

NASA NTRS2000

The Dynamic Planner: The Sequencer, Scheduler, and Runway Allocator for Air Traffic Control Automation

The Dynamic Planner (DP) has been designed, implemented, and integrated into the Center-TRACON Automation System (CTAS) to assist Traffic Management Coordinators (TMCs), in real time, with the task of planning and scheduling arrival traffic approximately 35 to 200 nautical miles from the destination airport. The TMC may input to the DP a series of current and future scheduling constraints that reflect the operation and environmental conditions of the airspace. Under these constraints, the DP uses flight plans, track updates, and Estimated Time of Arrival (ETA) predictions to calculate optimal runway assignments and arrival schedules that help ensure an orderly, efficient, and conflict-free flow of traffic into the terminal area. These runway assignments and schedules can be shown directly to controllers or they can be used by other CTAS tools to generate advisories to the controllers. Additionally, the TMC and controllers may override the decisions made by the DP for tactical considerations. The DP will adapt to computations to accommodate these manual inputs.

Wong, Gregory L.↗

NASA NTRS2013

NextGen Operational Improvements: Will they Improve Human Performance

Modernization of the National Airspace System depends critically on the development of advanced technology, including cutting-edge automation, controller decision-support tools and integrated on-demand information. The Next Generation Air Transportation System national plan envisions air traffic control tower automation that proposes solutions for seven problems: 1) departure metering, 2) taxi routing, 3) taxi and runway scheduling, 4) departure runway assignments, 5) departure flow management, 6) integrated arrival and departure scheduling and 7) runway configuration management. Government, academia and industry are simultaneously pursuing the development of these tools. For each tool, the development process typically begins by assessing its potential benefits, and then progresses to designing preliminary versions of the tool, followed by testing the tool's strengths and weaknesses using computational modeling, human-in-the-loop simulation and/or field tests. We compiled the literature, evaluated the methodological rigor of the studies and served as referee for partisan conclusions that were sometimes overly optimistic. Here we provide the results of this review.

Beard, Bettina L.↗

NASA NTRS2015

A Stochastic Scheduler for Integrated Arrival, Departure and Surface Operations in Los Angeles

In terminal airspace, integrating arrivals, departures, and surface operations with competing resources provides the potential of improving operational efficiency by removing barriers between different operations. This work develops a centralized stochastic scheduler for operations in a terminal area including airborne and surface operations using Non-dominated sorting genetic algorithm and Monte Carlo simulations. The scheduler handles completing resources between different flows, such as runway allocations, runway crossing, departure fixes, and other interaction way points between arrivals and departures. Meanwhile, the scheduler also takes time-varied uncertainties into account when optimizing schedules. The scheduler is run sequentially to identify the best and robust schedule for the next planning window. Resulting schedules decide the routes, speed or delays, and runway assignments with separation constraints at mergingdiverging waypoints in the air and crossing and separations on runways. The Los Angels terminal area was used as an example. The implementation of this stochastic scheduler for integrated arrival, departure and surface operations is completed. And several preliminary runs are finished for over 1,200 flights in LAX in a typical day. Sensitivity studies on various planning window sizes are presented, which shows that trade-off exits between planning window size and achievable minimum delay. Preliminary results on runway usage are also presented in this abstract. Because arrivals on the outer runways have to be followed by crossings on the inner runways, algorithmic runway allocation prefers inner runways for arrivals and outer runways for departures. More results will be presented in the final paper. And current terminal arrival and departure procedures based on first-come-first-serve procedure will also be set up and used as a baseline for comparison.

integrated scheduler↗

NASA NTRS2017

Assessing Tactical Scheduler Options for Time-Based Surface Metering

NASA is committed to demonstrating a concept of integrated arrival, departure, and surface operations by 2020 under the Airspace Technology Demonstration 2 (ATD2) sub-project. This will be accomplished starting with a demonstration of flight specific time-based departure metering at Charlotte Douglass International Airport (CLT). ATD2 tactical metering capability is based on NASAs Spot And Runway Departure Advisor (SARDA) which has been tested successfully in human-in-the-loop simulations of CLT. SARDA makes use of surface surveillance data and surface modeling to estimate the earliest takeoff time for each flight active on the airport surface or ready for pushback from the gate. The system then schedules each flight to its assigned runway in order of earliest takeoff time and assigns a target pushback time, displayed to ramp controllers as an advisory gate hold time. The objective of this method of departure metering is to move as much delay as possible to the gate to minimize surface congestion and engine on-time, while keeping sufficient pressure on the runway to maintain throughput. This flight specific approached enables greater flight efficiency and predictability, facilitating trajectory-based operations and surface-airspace integration, which ATD2 aims to achieve.Throughout ATD2 project formulation and system development, researchers have continuously engaged with stakeholders and future users, uncovering key system requirements for tactical metering that SARDA did not address. The SARDA scheduler is updated every 10 seconds using real-time surface surveillance data to ensure the most up-to-date information is used to predict runway usage. However, rapid updates also open the potential for fluctuating advisories, which Ramp controllers at a busy airport like CLT find unacceptable. Therefore, ATD2 tactical metering requires that all advisories freeze once flights are ready so that Ramp controllers may communicate a single hold time when responding to pilot ready calls.

Zelinski, Shannon↗

NASA NTRS1993

Design of Center-TRACON Automation System

A system for the automated management and control of terminal area traffic, referred to as the Center-TRACON Automation System (CTAS), is being developed at NASA Ames Research Center. In a cooperative program, NASA and FAA have efforts underway to install and evaluate the system at the Denver area and Dallas/Ft. Worth area air traffic control facilities. This paper will review CTAS architecture, and automation functions as well as the integration of CTAS into the existing operational system. CTAS consists of three types of integrated tools that provide computer-generated advisories for both en-route and terminal area controllers to guide them in managing and controlling arrival traffic efficiently. One tool, the Traffic Management Advisor (TMA), generates runway assignments, landing sequences and landing times for all arriving aircraft, including those originating from nearby feeder airports. TMA also assists in runway configuration control and flow management. Another tool, the Descent Advisor (DA), generates clearances for the en-route controllers handling arrival flows to metering gates. The DA's clearances ensure fuel-efficient and conflict free descents to the metering gates at specified crossing times. In the terminal area, the Final Approach Spacing Tool (FAST) provides heading and speed advisories that help controllers produce an accurately spaced flow of aircraft on the final approach course. Data bases consisting of several hundred aircraft performance models, airline preferred operational procedures, and a three dimensional wind model support the operation of CTAS. The first component of CTAS, the Traffic Management Advisor, is being evaluated at the Denver TRACON and the Denver Air Route Traffic Control Center. The second component, the Final Approach Spacing Tool, will be evaluated in several stages at the Dallas/Fort Worth Airport beginning in October 1993. An initial stage of the Descent Advisor tool is being prepared for testing at the Denver Center in late 1994. Operational evaluations of all three integrated CTAS tools are expected to begin at the two field sites in 1995.

Erzberger, Heinz↗

NASA NTRS1995

Effects of ATC automation on precision approaches to closely space parallel runways

Improved navigational technology (such as the Microwave Landing System and the Global Positioning System) installed in modern aircraft will enable air traffic controllers to better utilize available airspace. Consequently, arrival traffic can fly approaches to parallel runways separated by smaller distances than are currently allowed. Previous simulation studies of advanced navigation approaches have found that controller workload is increased when there is a combination of aircraft that are capable of following advanced navigation routes and aircraft that are not. Research into Air Traffic Control automation at Ames Research Center has led to the development of the Center-TRACON Automation System (CTAS). The Final Approach Spacing Tool (FAST) is the component of the CTAS used in the TRACON area. The work in this paper examines, via simulation, the effects of FAST used for aircraft landing on closely spaced parallel runways. The simulation contained various combinations of aircraft, equipped and unequipped with advanced navigation systems. A set of simulations was run both manually and with an augmented set of FAST advisories to sequence aircraft, assign runways, and avoid conflicts. The results of the simulations are analyzed, measuring the airport throughput, aircraft delay, loss of separation, and controller workload.

Slattery, R.↗

NASA NTRS1994

The Final Approach Spacing Tool

A system for assisting terminal area air traffic controllers in the management and control of arrival traffic, referred to as the Final Approach Spacing Tool (FAST), is being developed at NASA Ames Research Center. In a cooperative program, NASA and FAA have efforts underway to install and evaluate the system at the Dallas/Fort Worth Terminal Radar Approach Control facility. This paper will review the software architecture, the algorithms components, and the human-machine interface. The system is based on continuous updates of a detailed trajectory analyses of all arrival aircraft. FAST interprets the results of these trajectory analyses to build an efficient and procedurally acceptable plan for the arrival traffic that consists of a sequence, schedule, and runway assignment. The system utilizes a heuristically-based conflict resolution algorithm to build a solution trajectory that satisfies the plan, It extracts a series of speed and heading advisories from the solution trajectory to assist the controller in efficiently managing and controlling the arrival traffic down to the runway. The advisories are displayed in a graphical format to the controller. In addition to the radar tracking data, the system also relies on a series of data bases. These data bases contain aircraft performance models, airline preferred operational procedures, airspace structure, air traffic procedural models, and a three dimensional wind model. Field evaluation of FAST is expected to begin in 1994.

Davis, Thomas J.↗

NASA NTRS1995

Knowledge-based scheduling of arrival aircraft

A knowledge-based method for scheduling arrival aircraft in the terminal area has been implemented and tested in real-time simulation. The scheduling system automatically sequences, assigns landing times, and assigns runways to arrival aircraft by utilizing continuous updates of aircraft radar data and controller inputs. The scheduling algorithms is driven by a knowledge base which was obtained in over two thousand hours of controller-in-the-loop real-time simulation. The knowledge base contains a series of hierarchical 'rules' and decision logic that examines both performance criteria, such as delay reduction, as well as workload reduction criteria, such as conflict avoidance. The objective of the algorithms is to devise an efficient plan to land the aircraft in a manner acceptable to the air traffic controllers. This paper will describe the scheduling algorithms, give examples of their use, and present data regarding their potential benefits to the air traffic system.

Krzeczowski, K.↗

NASA NTRS1995

Knowledge-Based Scheduling of Arrival Aircraft in the Terminal Area

A knowledge based method for scheduling arrival aircraft in the terminal area has been implemented and tested in real time simulation. The scheduling system automatically sequences, assigns landing times, and assign runways to arrival aircraft by utilizing continuous updates of aircraft radar data and controller inputs. The scheduling algorithm is driven by a knowledge base which was obtained in over two thousand hours of controller-in-the-loop real time simulation. The knowledge base contains a series of hierarchical 'rules' and decision logic that examines both performance criteria, such as delay reductions, as well as workload reduction criteria, such as conflict avoidance. The objective of the algorithm is to devise an efficient plan to land the aircraft in a manner acceptable to the air traffic controllers. This paper describes the scheduling algorithms, gives examples of their use, and presents data regarding their potential benefits to the air traffic system.

Krzeczowski, K. J.↗

NASA NTRS1996

Operational Test Results of the Final Approach Spacing Tool

A prototype decision support tool for terminal area air traffic controllers, referred to as the Final Approach Spacing Tool (FAST), was recently evaluated in operation with live air traffic at the Dallas/Fort Worth Terminal Radar Approach Control (TRACON) facility in the United States. Controllers utilized the FAST system's runway assignment and sequence advisories to manage and control arrival traffic during more than twenty five peak rush traffic periods. The system performed well resulting in capacity increases at the airport of 10-20% depending on weather and airport conditions. As a result of these tests, the US Federal Aviation Administration (FAA) is proceeding with plans to further develop the prototype FAST system for national deployment at five to ten TRACONs within the United States during the next five years. This paper will present the results of these tests including data on the FAST system impact on airport capacity, aircraft flight times in the terminal area, delay reduction, tower operations including ground movement, and human factors data including workload assessments.

Davis, Thomas J.↗

NASA NTRS1998

An Operational Concept for Flying FMS Trajectories in Center and TRACON Airspace

Current Flight Management Systems (FMS) do a good job of constructing and flying an optimal trajectory for a single aircraft. Unfortunately, flight crews are often unable to fly these FMS routes during arrivals at busy airports. The Center TRACON Automation System (CTAS) has been designed to aid Center and TRACON (Terminal Radar Approach Control) controllers in assigning runways, sequencing and vectoring all classes of aircraft. CTAS bases its advisories on trajectory predictions for arriving aircraft using algorithms very similar to those in airborne FMS systems. This paper presents near and far term operational concepts for how a ground ATM (air traffic management) automation system like CTAS could work more effectively with the airborne automation in FMS equipped aircraft. The concepts for a more compatible air-ground system include: 1) a common route databases for both CTAS and FMS; 2) datalink to downlink information on aircraft weight, final approach speed and trajectory intent and to uplink wind information; 3) new FMS functions to allow flight crews to easily update their FMS trajectory to match the trajectory suggested by the ground automation with voice clearances, and 4) in the far term, datalink to downlink user preferred trajectories and to uplink trajectory clearances in the terminal area. The paper analyses some of the human factors issues that may result in allowing aircraft to fly FMS routes during enroute descent and in the terminal area. A series of linked human in the loop flight deck and air traffic control simulations and a field test with the NASA 757 are being conducted at NASA's Ames and Langley Research Centers to address these issues and to evaluate the operational feasibility of these approaches to more efficient flight and increased airport throughput.

Palmer, Everett↗

NASA NTRS2013

Precision Departure Release Capability (PDRC) Final Report

After takeoff, aircraft must merge into en route (Center) airspace traffic flows that may be subject to constraints that create localized demand/capacity imbalances. When demand exceeds capacity, Traffic Management Coordinators (TMCs) and Frontline Managers (FLMs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves a Call for Release (CFR) procedure wherein the Tower must call the Center to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool, based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release time is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that improves tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions and departure runway assignments to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept reduces uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs and FLMs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station in Dallas/Fort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations. This paper presents research results from the PDRC research activity. Companion papers present the Concept of Operations and a Technology Description.

tactical departure scheduling↗

NASA NTRS2013

Precision Departure Release Capability (PDRC): NASA to FAA Research Transition

After takeoff, aircraft must merge into en route (Center) airspace traffic flows which may be subject to constraints that create localized demand-capacity imbalances. When demand exceeds capacity, Traffic Management Coordinators (TMCs) and Frontline Managers (FLMs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves use of a Call for Release (CFR) procedure wherein the Tower must call the Center to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release time is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that improves tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions and departure runway assignments to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept reduces uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs and FLMs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station in Dallas-Fort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations.

ATM↗

NASA NTRS2013

Precision Departure Release Capability (PDRC) Overview and Results: NASA to FAA Research Transition

NASA researchers developed the Precision Departure Release Capability (PDRC) concept to improve the tactical departure scheduling process. The PDRC system is comprised of: 1) a surface automation system that computes ready time predictions and departure runway assignments, 2) an en route scheduling automation tool that uses this information to estimate ascent trajectories to the merge point and computes release times and, 3) an interface that provides two-way communication between the two systems. To minimize technology transfer issues and facilitate its adoption by TMCs and Frontline Managers (FLM), NASA developed the PDRC prototype using the Surface Decision Support System (SDSS) for the Tower surface automation tool, a research version of the FAA TMA (RTMA) for en route automation tool and a digital interface between the two DSTs to facilitate coordination.

PDRC↗

NASA NTRS2016

Human-In-The-Loop Investigation of Interoperability Between Terminal Sequencing and Spacing, Automated Terminal Proximity Alert, and Wake-Separation Recategorization

A human-in-the-loop simulation study addressed terminal-area controller-workstation interface variations for interoperability between three new capabilities being introduced by the FAA. The capabilities are Terminal Sequencing and Spacing (TSAS), Automated Terminal Proximity Alert (ATPA), and wake-separation recategorization, or 'RECAT.' TSAS provides controllers with Controller-Managed Spacing (CMS) tools, including slot markers, speed advisories, and early/late indications, together with runway assignments and sequence numbers. ATPA provides automatic monitor, warning, and alert cones to inform controllers about spacing between aircraft on approach. ATPA cones are sized according to RECAT, an improved method of specifying wake-separation standards. The objective of the study was to identify potential issues and provide recommendations for integrating TSAS with ATPA and RECAT. Participants controlled arrival traffic under seven different display configurations, then tested an 'exploratory' configuration developed with participant input. All the display conditions were workable and acceptable, but controllers strongly preferred having the CMS tools available on Feeder positions, and both CMS tools and ATPA available on Final positions. Controllers found the integrated systems favorable and liked being able to tailor configurations to individual preferences.

ATD-1↗

NASA NTRS2011

TPSAS-NF1676L-12441-DND

The increasing presence of airport surface surveillance technologies has spawned a strong interest in airport surface traffic management research; the vast majority has assumed that the airport’s runway configuration is known and constant. Tactical Runway Configuration Management (TRCM), one component of NASA’s System Oriented Runway Management concept, plans the airport configuration to optimize traffic efficiency for the forecast weather, traffic, and other factors. While planning runway configuration can provide benefit and is required by other automation concepts, larger benefits are possible by planning other airport configuration decisions, such as runway assignment policies, that are currently made manually by controllers. A laboratory prototype of the TRCM algorithm which selects optimal airport configuration schedules has been implemented and studied within a simulation environment. The presentation will describe simulation results for several airports, under various weather and traffic conditions. The sequence of airport configurations recommended by TRCM result in significantly less delay than the airport configurations that were actually used by controllers, illustrating both the potential benefit from airport configuration optimization and the ability of TRCM to provide effective airport configuration schedules. The application to several, distinct airports demonstrates the approach is capable of handling the differences between airports with a common algorithm, while providing decision support that respects the current procedures at those airports. Consequently, TRCM is able to be deployed to any airport within the current National Airspace System. The TRCM algorithmic approach is also extensible to future operational scenarios. NASA is in the process of transferring the initial TRCM technology to the FAA. Future research will extend the concept and algorithm to provide coordinated plans for metroplex airports and study NextGen applications.

Stephen Atkins↗