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NASA NTRSDate not supplied

Ground-Based Vision Tracker for Advanced Air Mobility and Urban Air Mobility

Advanced Air Mobility (AAM) Air Mobility and Urban Air Mobility (UAM) require aircraft surveillance and monitoring for safety and security. Persistent tracking of flying objects provides Air Traffic Control (ATC) and Air Traffic Management (ATM) continuous coverage and knowledge of the national airspace (NAS). Since there are numerous more AAM and UAM aircraft than commercial aircraft, it will be challenging to utilize the same ATC/ATM architectures. A first step in creating a similar ATC/ATM architecture for AAM/UAM will require ground-based and airborne-based sensors to provide monitoring, which will be difficult in urban environments due to GPS degradation. This paper proposes a vision-based tracking method with static cameras by utilizing image subtraction and blob detection, which avoids adding additional electromagnetic interferences in the environment with sensors such as radar. The ground-based vision tracker (GBVT) outputs the detected objects' azimuth and elevation angles from unmanned aerial system (UAS) flight tests. Future and ongoing work includes sending the detected objects' azimuth and elevation angles as inputs for an extended Kalman filter (EKF) to estimate the position and velocity of the detected object.

distributed sensing↗

NASA NTRSDate not supplied

Ground-Based Vision Tracker for Advanced Air Mobility and Urban Air Mobility

Advanced Air Mobility (AAM) Air Mobility and Urban Air Mobility (UAM) require aircraft surveillance and monitoring for safety and security. Persistent tracking of flying objects provides Air Traffic Control (ATC) and Air Traffic Management (ATM) continuous coverage and knowledge of the national airspace system (NAS). Given the significant disparity in the number of AAM and UAM aircraft compared to commercial aircraft in the NAS, coupled with the dense AAM/UAM operations in urban environments, employing the existing ATC/ATM architectures poses considerable challenges. A first step in creating a similar ATC/ATM architecture for AAM/UAM will require ground-based and airborne-based sensors to provide monitoring, which will be difficult in urban environments due to GPS degradation. This paper proposes a vision-based tracking method with static cameras by utilizing image subtraction and blob detection, which avoids adding additional electromagnetic interferences in the environment with sensors such as radar. The ground-based vision tracker (GBVT) outputs the detected objects' azimuth and elevation angles from unmanned aerial system (UAS) flight tests. Future and ongoing work includes sending the detected objects' azimuth and elevation angles as inputs for an extended Kalman filter (EKF) to estimate the position and velocity of the detected object.

distributed sensing↗

NASA NTRS2016

Benefits of Using Pairwise Trajectory Management in the Central East Pacific

Pairwise Trajectory Management (PTM) is a concept that utilizes airborne and ground-based capabilities to enable airborne spacing operations in oceanic regions. The goal of PTM is to use enhanced surveillance, along with airborne tools, to manage the spacing between aircraft. Due to the enhanced airborne surveillance of Automatic Dependent Surveillance-Broadcast (ADS-B) information and reduced communication, the PTM minimum spacing distance will be less than distances currently required of an air traffic controller. Reduced minimum distance will increase the capacity of aircraft operations at a given altitude or volume of airspace, thereby increasing time on desired trajectory and overall flight efficiency. PTM is designed to allow a flight crew to resolve a specific traffic conflict (or conflicts), identified by the air traffic controller, while maintaining the flight crew's desired altitude. The air traffic controller issues a PTM clearance to a flight crew authorized to conduct PTM operations in order to resolve a conflict for the pair (or pairs) of aircraft (i.e., the PTM aircraft and a designated target aircraft). This clearance requires the flight crew of the PTM aircraft to use their ADS-B-enabled onboard equipment to manage their spacing relative to the designated target aircraft to ensure spacing distances that are no closer than the PTM minimum distance. When the air traffic controller determines that PTM is no longer required, the controller issues a clearance to cancel the PTM operation.

Chartrand, Ryan↗

NASA NTRS1996

A Task-Analytic Approach to the Determination of Training Requirements for the Precision Descent

A task-analytic approach was used to evaluate the results from an experiment comparing two training methods for the "Precision Descent," a cockpit procedure designed to complement a new, computer-based air traffic control advisory system by allowing air traffic controllers to assign precise descent trajectories to aircraft. A task model was developed for the procedure using a methodology that represents four different categories of task-related knowledge: (1) ability to determine current flight goals; (2) ability to assess the current flight situation relative to those goals; (3) operational knowledge about flight-related tasks; and (4) knowledge about task selection. This model showed what knowledge experienced pilots already possessed, and how that knowledge was supplemented by training material provided in the two training conditions. All flight crews were given a "Precision Descent Chart" that explained the procedure's clearances and compliance requirements. This information enabled pilots to establish appropriate flight goals for the descent, and to monitor their compliance with those goals. In addition to this chart, half of the crews received a "Precision Descent Bulletin" containing technique recommendations for performing procedure-related tasks. The Bulletin's recommendations supported pilots in task selection and helped clarify the procedure's compliance requirements. Eight type-rated flight crews flew eight Precision Descents in a Boeing 747-400 simulator, with four crews in each of the two training conditions. Both conditions (Chart and Chart-with-Bulletin) relied exclusively on the use of those documents to introduce the procedure. No performance feedback was provided during the experiment. Preliminary result show better procedure compliance and higher acceptability ratings from flight crews in the Chart-with-Bulletin condition. These crews performed flight-related tasks less efficiently, however, using the simpler but less efficient methods suggested in the Bulletin. When a more efficient method was recognized, these crews tended to use the more efficient method in addition to the Bulletin's recommendation, instead of replacing it.

Smith, Nancy↗

NASA NTRS2012

Air Traffic Management Research at NASA

The U.S. air transportation system is the most productive in the world, moving far more people and goods than any other. It is also the safest system in the world, thanks in part to its venerable air traffic control system. But as demand for air travel continues to grow, the air traffic control systems aging infrastructure and labor-intensive procedures are impinging on its ability to keep pace with demand. And that impinges on the growth of our economy. Part of NASA's current mission in aeronautics research is to invent new technologies and procedures for ATC that will enable our national airspace system to accommodate the increasing demand for air transportation well into the next generation while still maintaining its excellent record for safety. It is a challenging mission, as efforts to modernize have, for decades, been hamstrung by the inability to assure safety to the satisfaction of system operators, system regulators, and/or the traveling public. In this talk, we'll provide a brief history of air traffic control, focusing on the tension between efficiency and safety assurance, and we'll highlight some new NASA technologies coming down the pike.

Farley, Todd↗

NASA NTRS2013

Pilot and Controller Evaluations of Separation Function Allocation in Air Traffic Management

Two human-in-the-loop simulation experiments were conducted in coordinated fashion to investigate the allocation of separation assurance functions between ground and air and between humans and automation. The experiments modeled a mixed-operations concept in which aircraft receiving ground-based separation services shared the airspace with aircraft providing their own separation service (i.e., self-separation). Ground-based separation was provided by air traffic controllers without automation tools, with tools, or by ground-based automation with controllers in a managing role. Airborne self-separation was provided by airline pilots using self-separation automation enabled by airborne surveillance technology. The two experiments, one pilot-focused and the other controller-focused, addressed selected key issues of mixed operations, assuming the starting point of current-day operations and modeling an emergence of NextGen technologies and procedures. In the controller-focused experiment, the impact of mixed operations on controller performance was assessed at four stages of NextGen implementation. In the pilot-focused experiment, the limits to which pilots with automation tools could take full responsibility for separation from ground-controlled aircraft were tested. Results indicate that the presence of self-separating aircraft had little impact on the controllers' ability to provide separation services for ground-controlled aircraft. Overall performance was best in the most automated environment in which all aircraft were data communications equipped, ground-based separation was highly automated, and self-separating aircraft had access to trajectory intent information for all aircraft. In this environment, safe, efficient, and highly acceptable operations could be achieved for twice today's peak airspace throughput. In less automated environments, reduced trajectory intent exchange and manual air traffic control limited the safely achievable airspace throughput and negatively impacted the maneuver efficiency of self-separating aircraft through high-density airspace. In a test of scripted conflicts with ground-managed aircraft, flight crews of self-separating aircraft prevented separation loss in all conflicts with detection time greater than one minute. In debrief, pilots indicated a preference for at least five minute's alerting notice and trajectory intent information on all aircraft. When intent information on ground-managed aircraft was available, self-separating aircraft benefited from fewer conflict alerts and fewer required deviations from trajectory-based operations.

Wing, David↗

NASA NTRS1995

The development of the Final Approach Spacing Tool (FAST): A cooperative controller-engineer design approach

Historically, the development of advanced automation for air traffic control in the United States has excluded the input of the air traffic controller until the need of the development process. In contrast, the development of the Final Approach Spacing Tool (FAST), for the terminal area controller, has incorporated the end-user in early, iterative testing. This paper describes a cooperative between the controller and the developer to create a tool which incorporates the complexity of the air traffic controller's job. This approach to software development has enhanced the usability of FAST and has helped smooth the introduction of FAST into the operational environment.

Lee, Katharine K.↗

NASA NTRS2003

En Route Descent Advisor Multi-Sector Planning Using Active and Provisional Controller Plans

As decision support tools are developed to support controllers in complex air traffic control environments, new approaches to maintaining situation awareness and managing traffic planning must be developed to handle the ever-increasing amounts of alerting and advisory data. Within high-density metering and other environments where flight path changes are the rule, not the exception, and where interactions between these changes are required, current trial planning approaches are limited by potential increases in workload. The Enroute Descent Advisor (EDA) is a set of decision support tool capabilities for managing high-density en route traffic subject to metering restrictions. The EDA system s novel approach builds aircraft plans from combinations of user intent data and builds controller plans from combinations of aircraft plans to effectively maintain situation awareness during traffic planning. By maintaining both active (current) and provisional (proposed) controller plans, EDA supports controllers in coordinated traffic planning both within and between sectors. Ultimately, EDA s multi-sector planning approach will facilitate a transition from current sector-oriented operations to a new trajectory-oriented paradigm, enabling new levels of efficiency and collaboration in air traffic control.

Vivona, Robert↗

NASA NTRS2005

STS-114: Discovery Mission Status Briefing

This video features mid-deck payloads being stowed at Pad 39B, a ribbon cutting ceremony at the NASA Shuttle Launch Facility (SLF) Air Traffic Control Tower and footage of the air traffic control radar constructed at Shiloh. The STS-114 Crewmembers, Commander, Eileen Collins, Pilot, James Kelly, Mission Specialist, Charles Camarda, Mission Specialist, Wendy Lawrence, Mission Specialist, Soichi Noguchi, JAXA, Mission Specialist, Stephen Robinson, and Mission Specialist Andrew Thomas are shown arriving at the Shuttle Landing Facility at Kennedy Space Center. Eileen Collins introduces each crew member and talks to the news media about their role during this mission. The astronauts are also shown during their spacesuit fit check at the Operations and Control Center (O&C) and footage of a practice flight is presented. The start of the countdown clock in the firing room 3 of the launch control center is shown

Source record↗

NASA NTRS2012

Comparison of Predictive Modeling Methods of Aircraft Landing Speed

Expected increases in air traffic demand have stimulated the development of air traffic control tools intended to assist the air traffic controller in accurately and precisely spacing aircraft landing at congested airports. Such tools will require an accurate landing-speed prediction to increase throughput while decreasing necessary controller interventions for avoiding separation violations. There are many practical challenges to developing an accurate landing-speed model that has acceptable prediction errors. This paper discusses the development of a near-term implementation, using readily available information, to estimate/model final approach speed from the top of the descent phase of flight to the landing runway. As a first approach, all variables found to contribute directly to the landing-speed prediction model are used to build a multi-regression technique of the response surface equation (RSE). Data obtained from operations of a major airlines for a passenger transport aircraft type to the Dallas/Fort Worth International Airport are used to predict the landing speed. The approach was promising because it decreased the standard deviation of the landing-speed error prediction by at least 18% from the standard deviation of the baseline error, depending on the gust condition at the airport. However, when the number of variables is reduced to the most likely obtainable at other major airports, the RSE model shows little improvement over the existing methods. Consequently, a neural network that relies on a nonlinear regression technique is utilized as an alternative modeling approach. For the reduced number of variables cases, the standard deviation of the neural network models errors represent over 5% reduction compared to the RSE model errors, and at least 10% reduction over the baseline predicted landing-speed error standard deviation. Overall, the constructed models predict the landing-speed more accurately and precisely than the current state-of-the-art.

Diallo, Ousmane H.↗

NASA NTRS2017

Management by Trajectory Trade Study of Roles and Responsibilities Between Participants and Automation Report

This report describes a trade study of roles and responsibilities associated with the Management by Trajectory (MBT) concept. The MBT concept describes roles, responsibilities, and information and automation requirements for providing air traffic controllers and managers the ability to quickly generate, evaluate and implement changes to an aircraft's trajectory. In addition, the MBT concept describes mechanisms for imposing constraints on flight operator preferred trajectories only to the extent necessary to maintain safe and efficient traffic flows, and the concept provides a method for the exchange of trajectory information between ground automation systems and the aircraft that allows for trajectory synchronization and trajectory negotiation. The participant roles considered in this trade study include: airline dispatcher, flight crew, radar controller, traffic manager, and Air Traffic Control System Command Center (ATCSCC) traffic management specialists. The proposed allocation of roles and responsibilities was based on analysis of several use cases that were developed for this purpose as well as for walking through concept elements. The resulting allocation of roles and responsibilities reflects both increased automation capability to support many aviation functions, as well as increased flexibility to assign responsibilities to different participants - in many cases afforded by the increased automation capabilities. Note that the selection of participants to consider for allocation of each function is necessarily rooted in the current environment, in that MBT is envisioned as an evolution of the National Airspace System (NAS), and not a revolution. A key feature of the MBT allocations is a vision for the traffic management specialist to take on a greater role. This is facilitated by the vision that separation management functions, in addition to traffic management functions, will be carried out as trajectory management functions. This creates an opportunity for flexibility, allowing the traffic management specialist to carry out tasks that today can only be carried out by the controller currently in contact with the aircraft. This additional tasking for the traffic management specialist comes with requirements for workload management. An increased role for the Data-side (D-side) controller relative to the Radar-side (R-side) controller is a potential approach to mitigating workload for the traffic management specialist, as the D-side controller would have similar ability to perform separation management functions in what today might be considered the "trajectory management" timeframe. This analysis did not distinguish between the D-side and R-side controllers since in many cases the R-side controller works unassisted.

Fernandes, Alicia D.↗

NASA NTRS1983

Flight management systems - What are they and why are they being developed?

This paper presents the motivation for developing and using flight management systems. The architecture and theoretical basis of these systems is presented and their typical operation during a flight is described. Two computer programs developed to support flight management research are used to obtain numerical results which illustrate significant potential reductions in fuel used and/or airline operating costs which can be achieved through use of flight management systems. The specific levels of savings depend on the nature of the air traffic control system in which the aircraft operates. Accordingly, results are presented both for operations in the existing air traffic control system and in an air traffic control environment with reduced restrictions on airplane operations. The capability of airplanes equipped with suitable flight management systems to operate in a time-based (4-D) environment is also discussed. Programs of the Federal Aviation Administration which may influence the operation of flight management system equipped aircraft in the evolving National Airspace System are also briefly reviewed.

Creedon, J. F.↗

NASA NTRS1995

TRACON Aircraft Arrival Planning and Optimization Through Spatial Constraint Satisfaction

A new aircraft arrival planning and optimization algorithm has been incorporated into the Final Approach Spacing Tool (FAST) in the Center-TRACON Automation System (CTAS) developed at NASA-Ames Research Center. FAST simulations have been conducted over three years involving full-proficiency, level five air traffic controllers from around the United States. From these simulations an algorithm, called Spatial Constraint Satisfaction, has been designed, coded, undergone testing, and soon will begin field evaluation at the Dallas-Fort Worth and Denver International airport facilities. The purpose of this new design is an attempt to show that the generation of efficient and conflict free aircraft arrival plans at the runway does not guarantee an operationally acceptable arrival plan upstream from the runway -information encompassing the entire arrival airspace must be used in order to create an acceptable aircraft arrival plan. This new design includes functions available previously but additionally includes necessary representations of controller preferences and workload, operationally required amounts of extra separation, and integrates aircraft conflict resolution. As a result, the Spatial Constraint Satisfaction algorithm produces an optimized aircraft arrival plan that is more acceptable in terms of arrival procedures and air traffic controller workload. This paper discusses the current Air Traffic Control arrival planning procedures, previous work in this field, the design of the Spatial Constraint Satisfaction algorithm, and the results of recent evaluations of the algorithm.

Bergh, Christopher P.↗

NASA NTRS2018

A Markov Decision Process Framework for Optimal Airport Reconfiguration

The airport runway configuration is defined as a combination set of runways for arrivals and departures used at a point during operation of the airport. An optimal configuration of these runways depends on a number of factors, including traffic demand, wind magnitude and direction, other adverse weather conditions, and noise restrictions, among others. Based on the current state of these factors and predictions of traffic demand and weather conditions, runway configuration changes are made and coordinated between tower controller, other air traffic control facilities, pilots, and ground personnel. Reconfigurations can be quite disruptive to airport operations; minimizing their frequency and scheduling them well in advance is essential for mitigating some of the added workload for controllers and pilots. Unfortunately, deciding on an appropriate time to change is challenging for human decision makers. Not only do multiple factors need to be evaluated, but the uncertainty in their forecasts must also be considered. Previous optimization methods, such as mixed linear integer programming, have been proposed. Although these methods can reason over a large set of variables, they do not systematically handle the uncertainty associated with weather movement, traffic demands, and other variables. In this work, we introduce a Markov Decision Process (MDP)-based decision making framework which can reason effectively over the inherent uncertainties and make optimal decisions on if/when to change the airport configuration. In a prototype implementation, we present a single runway with three aircraft and utilize knowledge of the forecasted wind speed and direction to determine whether to keep or change the current runway configuration. Our aim through this work is to present a framework for airport reconfiguration which can be scalable to additional aircraft, multiple runways, and various input parameters. This technique will optimize the airport reconfiguration procedure by providing a proactive approach, optimizing not just at the next optimal opportunity for a reconfiguration based on varying atmospheric and traffic conditions in the terminal airspace, but also anticipating future necessary reconfigurations. This will eliminate the inefficiencies of frequent changes currently associated with runway reconfiguration procedures.

runway reconfiguration↗

NASA NTRS1983

Development of real-time ATC simulation facility

The Flight Transportation Laboratory has developed a real time interactive Air Traffic Control simulation facility designed to provide a versatile and easy to use tool for research and experimentation involving air traffic control. The facility uses a VAX-11/750 as the central computer. The SANDERS GRAPHICS-7 display system is used to simulate air traffic control displays. Pseudo-pilot displays are provided on Texas Instruments TI940 video terminals. Finally, a custom designed audio system driven by a Z-80 and interfaced with the VAX provides voice communication between the air traffic controllers and the pseudo-pilots. The audio system provides computer controlled voice disguising and thus allows each aircraft to have its own audio characteristics and provides an added realism to the experiment. The facility can accommodate multiple controller stations and pseudo-pilot stations. Each station is manned by a single operator who has a large repertoire of commands with which to control his/her display and the simulated aircraft under his/her jurisdiction. An additional console and a distinct set of commands allow full controllability of the simulation environment by the experimenter in real time.

Pararas, J.↗

NASA NTRS2018

Designing Graceful Degradation into Complex Systems: The Interaction Between Causes of Degradation and the Association with Degradation Prevention and Recovery

System resilience is critical to safety in air traffic control. An important element of maintaining resilience is the ability of systems to degrade gracefully. Of the available graceful degradation research, a majority of studies have focused primarily on technological causes of degradation only, limiting an ecologically valid understanding of the causes of degradation in air traffic control, and the preventative and mitigative strategies that enable graceful degradation. The current study aimed to address this research gap by investigating causes of degradation in air traffic control across the broad categories of technology, the environment, and the human operator, and the potential interactions between these causes. 12 retired controllers participated in semi-structured interviews focused on previous experience of causes of degradation and mitigation strategies. Findings provide an understanding of causation of degradation in air traffic control, and the prevention and mitigation strategies that moderate the relationship between cause and system effect. Findings confirmed that causes appear to interact to create compound, multiple effects on overall system performance. Findings also revealed prevention and mitigation strategies utilized to moderate the effect of the cause on the system. In order to gain an ecologically valid understanding of the causes of degradation, and effective prevention or mitigation strategies, causes from multiple categories, and the interactions between them, must be identified. Findings have implications for designers of future air traffic control systems to ensure the ability of the system to gracefully degrade, as well as risk assessment and system validation processes.

human performance↗

NASA NTRSDate not supplied

Introduction to Air Traffic Management

The presentation introduces students and faculty to air traffic management with focus on air traffic data for data-science. Starting with the common attributes of transportation systems — highway transportation, air transportation and data transportation, the initial set of slides discuss the purpose of data-science in air traffic management, reasons why air traffic management is challenging, and the multidisciplinary nature of air traffic management research. The history of flight from 1903 — Wright Flyer — to 1987 — formation of the National Air Traffic Controllers Association — is briefly discussed. The national airspace system is described in terms of airports in the U. S., air traffic control facilities (flight service stations, terminal, enroute and system command center), airspace geometry (sectors, airways and navaids), governing regulations and directives, airspace classification (Class A through G), special use airspace, visual flight rules and instrument flight rules. The contents of a flight-plan are described. Weather briefing is discussed. The surveillance equipment used for surface, terminal area and enroute are described, and the aircraft states obtained using the surveillance data are listed. Airline operations control functions — schedule development, flight planning, resource scheduling and flight following — are noted. Next, the roles and responsibilities of air traffic controllers and traffic flow managers are discussed. Separation standards and conflict resolution techniques are outlined. Finally, traffic flow management techniques are reviewed with an illustrative example.

Air Traffic Management↗

NASA NTRSDate not supplied

Introduction to Air Traffic Management

Air Traffic Management↗