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NASA NTRS2021

A Machine Learning Approach to Predict Aircraft Landing Times using Mediated Predictions from Existing Systems

We developed a novel approach for predicting the landing time of airborne flights in real-time operations. The first step predicts a landing time by using mediation rules to select from among physics-based predictions (relying on the expected flight trajectory) already available in real time in the Federal Aviation Administration System Wide Information Management system data feeds. The second step uses a machine learning model built upon the mediated predictions. The model is trained to predict the error in the mediated prediction, using features describing the current state of an airborne flight. These features are calculated in real time from a relatively small number of data elements that are readily available for airborne flights. Initial results based on five months of data at six large airports demonstrate that incorporating a machine learning model on top of the mediated physics-based prediction can lead to substantial additional improvements in prediction quality.

Machine learning↗
NASA NTRS2010

Optimizing Flight Departure Delay and Route Selection Under En Route Convective Weather

This paper presents a linear Integer Programming model for managing air traffic flow in the United States. The decision variables in the model are departure delays and predeparture reroutes of aircraft whose trajectories are predicted to cross weather-impacted regions of the National Airspace System. The model assigns delays to a set of flights while ensuring their trajectories are free of any conflicts with weather. In a deterministic setting, there is no airborne holding due to unexpected weather incursion in a flight s path. The model is applied to solve a large-scale traffic flow management problem with realistic weather data and flight schedules. Experimental results indicate that allowing rerouting can reduce departure delays by nearly 57%, but it is associated with an increase in total airborne time due to longer routes flown by aircraft. The computation times to solve this problem were significantly lower than those reported in the earlier studies.

Mukherjee, Avijit↗
NASA NTRS2018

Using an Automated Air Traffic Simulation Capability for a Parametric Study in Traffic Flow Management

Flight delays occur when demand for capacity-constrained airspace or airports exceeds predicted capacity. Demand for capacity-constrained airspace or airports can be controlled by a series of Traffic Management Initiatives (TMIs), which use departure and airborne delays, as well as pre-departure and airborne reroutes, to manage access to the constrained resources. Two systems exist in current and planned future operations to address imbalances between demand and capacity. The Collaborative Trajectory Options Program (CTOP) reduces demand to constrained resources by assigning strategic departure delay and pre-departure reroutes. Reroutes are selected from Trajectory Options Sets (TOSs) submitted by airlines. As flights approach the constrained resource, the Time-Based Flow Management System (TBFM) is used to assign tactical delay to satisfy constraints. This paper describes experiments performed to study the impact of varying levels of airline participation in CTOP via submission of TOSs on ground delay and flight time, and the impact of departure uncertainty on TBFM delays. Results suggest that as CTOP participation increases, average ground delays decrease for all airlines, but to the greatest extent for airlines participating in CTOP. A threshold in CTOP participation, which varies with the constraint capacity, is identified beyond which there is relatively little further reduction in average ground delays. Similarly, given the likely level of CTOP participation, the capacity reduction for which CTOP would be an appropriate TMI is also identified. Results also suggest that high average departure errors and high variability in departure error can make the prioritization of TBFM internal departures in TBFM metering and scheduling infeasible. Departure errors at current levels are, however, acceptable.

CTOP↗
NASA NTRS2018

Using an Automated Air Traffic Simulation Capability for a Parametric Study in Traffic Flow Management

Flight delays occur when demand for capacity-constrained airspace or airports exceeds predicted capacity. Demand for capacity-constrained airspace or airports can be controlled by a series of Traffic Management Initiatives (TMIs), which use departure and airborne delays, as well as pre-departure and airborne reroutes, to manage access to the constrained resources. Two systems exist in current and planned future operations to address imbalances between demand and capacity. The Collaborative Trajectory Options Program (CTOP) reduces demand to constrained resources by assigning strategic departure delay and pre-departure reroutes. Reroutes are selected from Trajectory Options Sets (TOSs) submitted by airlines. As flights approach the constrained resource, the Time-Based Flow Management System (TBFM) is used to assign tactical delay to satisfy constraints. This paper describes experiments performed to study the impact of varying levels of airline participation in CTOP via submission of TOSs on ground delay and flight time, and the impact of departure uncertainty on TBFM delays. Results suggest that as CTOP participation increases, average ground delays decrease for all airlines, but to the greatest extent for airlines participating in CTOP. A threshold in CTOP participation, which varies with the constraint capacity, is identified beyond which there is relatively little further reduction in average ground delays. Similarly, given the likely level of CTOP participation, the capacity reduction for which CTOP would be an appropriate TMI is also identified. Results also suggest that high average departure errors and high variability in departure error can make the prioritization of TBFM internal departures in TBFM metering and scheduling infeasible. Departure errors at current levels are, however, acceptable.

integrated demand management↗
NASA NTRS1984

The flight planning - flight management connection

Airborne flight management systems are currently being implemented to minimize direct operating costs when flying over a fixed route between a given city pair. Inherent in the design of these systems is that the horizontal flight path and wind and temperature models be defined and input into the airborne computer before flight. The wind/temperature model and horizontal path are products of the flight planning process. Flight planning consists of generating 3-D reference trajectories through a forecast wind field subject to certain ATC and transport operator constraints. The interrelationships between flight management and flight planning are reviewed, and the steps taken during the flight planning process are summarized.

Sorensen, J. A.↗
NASA NTRS2011

An Overview of a Trajectory-Based Solution for En Route and Terminal Area Self-Spacing to Include Parallel Runway Operations

This paper presents an overview of an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This airborne self-spacing concept is trajectory-based, allowing for spacing operations prior to the aircraft being on a common path. This implementation provides the ability to manage spacing against two traffic aircraft, with one of these aircraft operating to a parallel dependent runway. Because this algorithm is trajectory-based, it also has the inherent ability to support required-time-of-arrival (RTA) operations

Abbott, Terence S.↗
NASA NTRS2009

Configuring a Graphical User Interface for Managing Local HYSPLIT Model Runs Through AWIPS

Responding to incidents involving the release of harmful airborne pollutants is a continual challenge for Weather Forecast Offices in the National Weather Service. When such incidents occur, current protocol recommends forecaster-initiated requests of NOAA's Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model output through the National Centers of Environmental Prediction to obtain critical dispersion guidance. Individual requests are submitted manually through a secured web site, with desired multiple requests submitted in sequence, for the purpose of obtaining useful trajectory and concentration forecasts associated with the significant release of harmful chemical gases, radiation, wildfire smoke, etc., into local the atmosphere. To help manage the local HYSPLIT for both routine and emergency use, a graphical user interface was designed for operational efficiency. The interface allows forecasters to quickly determine the current HYSPLIT configuration for the list of predefined sites (e.g., fixed sites and floating sites), and to make any necessary adjustments to key parameters such as Input Model. Number of Forecast Hours, etc. When using the interface, forecasters will obtain desired output more confidently and without the danger of corrupting essential configuration files.

Wheeler, mark M.↗
NASA NTRS2019

Using Machine-Learning to Dynamically Generate Operationally Acceptable Strategic Reroute Options

The newly developed Trajectory Option Set (TOS), a preference-weighted set of alternative routes submitted by flight operators, is a capability in the U.S. traffic flow management system that enables automated trajectory negotiation between flight operators and Air Navigation Service Providers. The objective of this paper is to describe and demonstrate an approach for automatically generating pre-departure and airborne TOSs that have a high probability of operational acceptance. The approach uses hierarchical clustering of historical route data to identify route candidates. The probability of operational acceptance is then estimated using predictors trained on historical flight plan amendment data using supervised machine learning algorithms, allowing the routes with highest probability of operational acceptance to be selected for the TOS. Features used describe historical route usage, difference in flight time and downstream demand to capacity imbalance. A random forest was found to be the best performing algorithm for learning operational acceptability, with a model accuracy of 0.96. The approach is demonstrated for an historical pre-departure flight from Dallas/Fort Worth International Airport to Newark Liberty International Airport.

Evans, Antony↗
NASA NTRS2019

Using Machine-Learning to Dynamically Generate Operationally Acceptable Strategic Reroute Options

The newly developed Trajectory Option Set (TOS), a preference-weighted set of alternative routes submitted by flight operators, is a capability in the U.S. traffic flow management system that enables automated trajectory negotiation between flight operators and Air Navigation Service Providers. The objective of this paper is to describe and demonstrate an approach for automatically generating pre-departure and airborne TOSs that have a high probability of operational acceptance. The approach uses hierarchical clustering of historical route data to identify route candidates. The probability of operational acceptance is then estimated using predictors trained on historical flight plan amendment data using supervised machine learning algorithms, allowing the routes with highest probability of operational acceptance to be selected for the TOS. Features used describe historical route usage, difference in flight time and downstream demand to capacity imbalance. A random forest was found to be the best performing algorithm for learning operational acceptability, with a model accuracy of 0.96. The approach is demonstrated for an historical pre-departure flight from Dallas/Fort Worth International Airport to Newark Liberty International Airport.

Evans, Antony↗
NASA NTRS2011

Research Of Airborne Precision Spacing to Improve Airport Arrival Operations

In September 2004, the European Organization for the Safety of Air Navigation (EUROCONTROL) and the United States Federal Aviation Administration (FAA) signed a Memorandum of Cooperation to mutually develop, modify, test, and evaluate systems, procedures, facilities, and devices to meet the need for safe and efficient air navigation and air traffic control in the future. In the United States and Europe, these efforts are defined within the architectures of the Next Generation Air Transportation System (NextGen) Program and Single European Sky Air Traffic Management Research (SESAR) Program respectively. Both programs have identified Airborne Spacing as a critical component, with Automatic Dependent Surveillance Broadcast (ADS-B) as a key enabler. Increased interest in reducing airport community noise and the escalating cost of aviation fuel has led to the use of Continuous Descent Arrival (CDA) procedures to reduce noise, emissions, and fuel usage compared to current procedures. To provide these operational enhancements, arrival flight paths into terminal areas are planned around continuous vertical descents that are closer to an optimum trajectory than those in use today. The profiles are designed to be near-idle descents from cruise altitude to the Final Approach Fix (FAF) and are typically without any level segments. By staying higher and faster than conventional arrivals, CDAs also save flight time for the aircraft operator. The drawback is that the variation of optimized trajectories for different types and weights of aircraft requires the Air Traffic Controller to provide more airspace around an aircraft on a CDA than on a conventional arrival procedure. This additional space decreases the throughput rate of the destination airport. Airborne self-spacing concepts have been developed to increase the throughput at high-demand airports by managing the inter-arrival spacing to be more precise and consistent using on-board guidance. It has been proposed that the additional space needed around an aircraft performing a CDA could be reduced or eliminated when using airborne spacing techniques.

Barmore, Bryan E.↗
NASA NTRS2020

Integrated Demand Management: Concepts and Procedures

This report provides a comprehensive description of the Integrated Demand Management concept. Motivation: NASA’s Integrated Demand Management (IDM) research explores the idea that, under certain conditions, time-based flow management (TBFM) arrival operations can benefit from the coordinated use of a strategic traffic management initiative (TMI) to “precondition” the inbound demand. The research was motivated by the observation that TBFM was usually turned off during convective weather, even in facilities where it was routinely used. Our hypothesis was that strategic adjustments to the inbound traffic so that it provided a better match to the off-nominal changes in capacity observed during these conditions could enable TBFM scheduling to continue to provide effective support for arrival traffic management. Concept: IDM proposes that a TMI (e.g., a Collaborative Trajectory Options Program, or CTOP) be used to adjust the rate and/or geographic distribution across flows of the traffic inbound to a high-demand, TBFM-managed airport before that traffic reaches the TBFM planning horizon. After this strategic preconditioning, TBFM can then tactically fine-tune the demand to deliver a well-managed, orderly feed to the destination airport. Coordinated use of these two flow management capabilities is intended to improve system performance in terms of: • Equity of ground delay assignment, avoiding excessive ground delay for TBFM-scheduled departures, without penalizing longer flights; • Throughput, by distributing traffic to maximize use of available capacity; • Predictability for operators, providing advance notice about the impact on individual flights; • Increased flexibility, supporting operator mitigation strategies such as slot swapping or trajectory options; • Efficiency of flight operations, using ground delay more effectively and reducing airborne delay. The operational description in this document highlights how the IDM concept builds upon already existing tools and procedures, and also indicates where tool enhancements could facilitate conduct of IDM operations. However, enhanced tools are not a requirement for concept introduction. In fact, initial deployment that focused on training procedures and rationale for coordinated use of TFMS and TBFM, without changes to existing tools, might be a simpler way to introduce and to familiarize traffic managers with the idea of preconditioning. The concept and procedures described in this document can hopefully provide useful guidance for introduction of IDM into field operations..

IDM↗
NASA NTRS2016

Airspace Technology Demonstration 3 (ATD-3): Dynamic Weather Routes (DWR) Technology Transfer Document Summary Version 1.0

Airspace Technology Demonstration #3 (ATD-3) is part of NASA's Airspace Operations and Safety Program (AOSP) - specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multiyear research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the first of three Research Transition Products (RTPs) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. This transfer consists of NASA's legacy Dynamic Weather Routes (DWR) work for efficient routing for en-route weather avoidance. DWR is a ground-based trajectory automation system that continuously and automatically analyzes active airborne aircraft in en route airspace to identify opportunities for simple corrections to flight plan routes that can save significant flying time, at least five minutes wind-corrected, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions. The key benefit of the DWR concept is to let automation continuously and automatically analyze active flights to find those where simple route corrections can save significant time and fuel. Operators are busy during weather events. It is more effective to let automation find the opportunities for high-value route corrections.

ATD-3↗
NASA NTRS2008

Performance Basis for Airborne Separation

Emerging applications of Airborne Separation Assistance System (ASAS) technologies make possible new and powerful methods in Air Traffic Management (ATM) that may significantly improve the system-level performance of operations in the future ATM system. These applications typically involve the aircraft managing certain components of its Four Dimensional (4D) trajectory within the degrees of freedom defined by a set of operational constraints negotiated with the Air Navigation Service Provider. It is hypothesized that reliable individual performance by many aircraft will translate into higher total system-level performance. To actually realize this improvement, the new capabilities must be attracted to high demand and complexity regions where high ATM performance is critical. Operational approval for use in such environments will require participating aircraft to be certified to rigorous and appropriate performance standards. Currently, no formal basis exists for defining these standards. This paper provides a context for defining the performance basis for 4D-ASAS operations. The trajectory constraints to be met by the aircraft are defined, categorized, and assessed for performance requirements. A proposed extension of the existing Required Navigation Performance (RNP) construct into a dynamic standard (Dynamic RNP) is outlined. Sample data is presented from an ongoing high-fidelity batch simulation series that is characterizing the performance of an advanced 4D-ASAS application. Data of this type will contribute to the evaluation and validation of the proposed performance basis.

Wing, David J.↗
NASA NTRS2009

Technology Advancements Enhance Aircraft Support of Experiment Campaigns

For over 30 years, the NASA Airborne Science Program has provided airborne platforms for space bound instrument development, for calibrating new and existing satellite systems, and for making in situ and remote sensing measurements that can only be made from aircraft. New technologies have expanded the capabilities of aircraft that are operated for these missions. Over the last several years a new technology investment portfolio has yielded improvements that produce better measurements for the airborne science communities. These new technologies include unmanned vehicles, precision trajectory control and advanced telecommunications capabilities. We will discuss some of the benefits of these new technologies and systems which aim to provide users with more precision, lower operational costs, quicker access to data, and better management of multi aircraft and multi sensor campaigns.

Vachon, Jacques J.↗
NASA NTRS2017

UAV Inspection of Electrical Transmission Infrastructure with Path Conformance Autonomy and Lidar-Based Geofences NASA Report on UTM Reference Mission Flights at Southern Company Flights November 2016

Flights at low altitudes in close proximity to electrical transmission infrastructure present serious navigational challenges: GPS and radio communication quality is variable and yet tight position control is needed to measure defects while avoiding collisions with ground structures. To advance unmanned aerial vehicle (UAV) navigation technology while accomplishing a task with economic and societal benefit, a high voltage electrical infrastructure inspection reference mission was designed. An integrated air-ground platform was developed for this mission and tested in two days of experimental flights to determine whether navigational augmentation was needed to successfully conduct a controlled inspection experiment. The airborne component of the platform was a multirotor UAV built from commercial off-the-shelf hardware and software, and the ground component was a commercial laptop running open source software. A compact ultraviolet sensor mounted on the UAV can locate 'hot spots' (potential failure points in the electric grid), so long as the UAV flight path adequately samples the airspace near the power grid structures. To improve navigation, the platform was supplemented with two navigation technologies: lidar-to-polyhedron preflight processing for obstacle demarcation and inspection distance planning, and trajectory management software to enforce inspection standoff distance. Both navigation technologies were essential to obtaining useful results from the hot spot sensor in this obstacle-rich, low-altitude airspace. Because the electrical grid extends into crowded airspaces, the UAV position was tracked with NASA unmanned aerial system traffic management (UTM) technology. The following results were obtained: (1) Inspection of high-voltage electrical transmission infrastructure to locate 'hot spots' of ultraviolet emission requires navigation methods that are not broadly available and are not needed at higher altitude flights above ground structures. (2) The sensing capability of a novel airborne UV detector was verified with a standard ground-based instrument. Flights with this sensor showed that UAV measurement operations and recording methods are viable. With improved sensor range, UAVs equipped with compact UV sensors could serve as the detection elements in a self-diagnosing power grid. (3) Simplification of rich lidar maps to polyhedral obstacle maps reduces data volume by orders of magnitude, so that computation with the resultant maps in real time is possible. This enables real-time obstacle avoidance autonomy. Stable navigation may be feasible in the GPS-deprived environment near transmission lines by a UAV that senses ground structures and compares them to these simplified maps. (4) A new, formally verified path conformance software system that runs onboard a UAV was demonstrated in flight for the first time. It successfully maneuvered the aircraft after a sudden lateral perturbation that models a gust of wind, and processed lidar-derived polyhedral obstacle maps in real time. (5) Tracking of the UAV in the national airspace using the NASA UTM technology was a key safety component of this reference mission, since the flights were conducted beneath the landing approach to a heavily used runway. Comparison to autopilot tracking showed that UTM tracking accurately records the UAV position throughout the flight path.

Moore, Andrew J.↗
NASA NTRS1993

Piloted simulation of an air-ground profile negotiation process in a time-based Air Traffic Control environment

Historically, development of airborne flight management systems (FMS) and ground-based air traffic control (ATC) systems has tended to focus on different objectives with little consideration for operational integration. A joint program, between NASA's Ames Research Center (Ames) and Langley Research Center (Langley), is underway to investigate the issues of, and develop systems for, the integration of ATC and airborne automation systems. A simulation study was conducted to evaluate a profile negotiation process (PNP) between the Center/TRACON Automation System (CTAS) and an aircraft equipped with a four-dimensional flight management system (4D FMS). Prototype procedures were developed to support the functional implementation of this process. The PNP was designed to provide an arrival trajectory solution which satisfies the separation requirements of ATC while remaining as close as possible to the aircraft's preferred trajectory. Results from the experiment indicate the potential for successful incorporation of aircraft-preferred arrival trajectories in the CTAS automation environment. Fuel savings on the order of 2 percent to 8 percent, compared to fuel required for the baseline CTAS arrival speed strategy, were achieved in the test scenarios. The data link procedures and clearances developed for this experiment, while providing the necessary functionality, were found to be operationally unacceptable to the pilots. In particular, additional pilot control and understanding of the proposed aircraft-preferred trajectory, and a simplified clearance procedure were cited as necessary for operational implementation of the concept.

Williams, David H.↗
NASA NTRS2018

Understanding Extended Projected Profile (EPP) Trajectory Error Using a Medium-Fidelity Aircraft Simulation

A critical component of Trajectory-Based Operations is the ability for a consistent and accurate 4-dimensional trajectory to be shared and synchronized between airborne and ground systems as well as amongst various ground automation systems. The Aeronautical Telecommunication Network—Baseline 2 standard defines the Extended Projected Profile (EPP) trajectory that can be sent via Automatic Dependent Surveillance-Contract from an aircraft to ground automation. The EPP trajectory message contains a representation of the reference trajectory from an aircraft’s Flight Management System (FMS). In this work, a set of scenarios were run in a medium-fidelity aircraft and FMS simulation to perform an initial characterization of EPP trajectory errors under a given set of conditions. The parameters investigated were the route length, route type, wind magnitude error, wind direction error, and with and without a required time-of-arrival constraint.

Guerreiro, Nelson M.↗
NASA NTRS2018

Preliminary Error Characterization and Parametric Error Model for the Automatic Dependent Surveillance - Contract Extended Projected Profile Message

A critical component of Trajectory-Based Operations (TBO) is the ability for a consistent and accurate 4-dimensional trajectory (4DT) to be shared and synchronized between airborne and ground systems as well as amongst various ground automation systems. The Aeronautical Telecommunication Network—Baseline 2 (ATN-B2) standard defines the Extended Projected Profile (EPP) trajectory that can be sent via Automatic Dependent Surveillance-Contract (ADS-C) from an aircraft to ground automation. The EPP trajectory message contains a representation of the reference trajectory from an aircraft’s Flight Management System (FMS). In this work, a set of scenarios were run in a high-fidelity aircraft and FMS simulation to perform an initial characterization of EPP trajectory errors under a given set of conditions. The parameters investigated were the route length, route type, wind magnitude error, wind direction error, and with and without a required time-of-arrival (RTA) constraint. In addition, linear regression was used to identify a set of EPP error models for the cross-track, vertical, and time errors.

Guerreiro, Nelson M.↗