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At least 253 records · Page 14

Identification and Development of Coordination Procedures Between Upper Class E Traffic Management (ETM) and Surrounding Air Traffic Operations

A recent interest in novel, non-traditional vehicles / missions that plan to operate in Upper Class E (UCE) airspace at or above 60,000 ft has led to efforts by NASA, FAA and the stakeholder communities to research and develop a new concept called Upper Class E Traffic Management (ETM). ETM concept proposes to handle the influx of diverse traffic mix around FL600 and above, utilizing a new traffic management infrastructure, supported by federated service suppliers that are developed by the community stakeholders, for coordinating, monitoring, and executing vehicle operational intent in a designated airspace called ETM Cooperative Area (CA). ETM vehicles are generally expected to reach and operate in ETM CA by first transiting through Class A airspace and potentially through UCE airspace that sits outside of ETM CA. In this paper, a set of use cases have been identified and step-by-step procedures have been developed to handle nominal transitions of ETM vehicles between these operational areas, as well as additional use cases and procedures for authorization and termination of ETM CAs in Class A and/or UCE airspace. The overall research effort in this paper has revealed potential challenges and open questions related to these use cases, especially for the interactions between ETM CA and UCE in both vehicle transition and ETM CA authorization scenarios. The use cases and procedures developed in this paper will inform future ETM integration efforts, as well as research and development into decision support tools needed for the integration.

Upper Class E Traffic Management (ETM)↗

A Fast-Time Study of Aircraft Reordering in Arrival Sequencing and Scheduling

In order to ensure that the safe capacity of the terminal area is not exceeded, Air Traffic Management ATM often places restrictions on arriving flights transitioning from en route airspace to terminal airspace. This restriction of arrival traffic is commonly referred to as arrival flow management, and includes techniques such as metering, vectoring, fix-load balancing, and the imposition of miles-in-trail separations. These restrictions are enacted without regard for the relative priority which airlines may be placing on individual flights based on factors such as crew criticality, passenger connectivity, critical turn times, gate availability, on-time performance, fuel status, or runway preference. The development of new arrival flow management techniques which take into consideration priorities expressed by air carriers will likely reduce the economic impact of ATM restrictions on the airlines and lead to increased airline economic efficiency by allowing airlines to have greater control over their individual arrival banks of aircraft. NASA and the Federal Aviation Administration (FAA) have designed and developed a suite of software decision support tools (DSTs) collectively known as the Center TRACON Automation System (CTAS). One of these tools, the Traffic Management Advisor (TMA) is currently being used at the Fort Worth Air Route Traffic Control Center to perform arrival flow management of traffic into the Dallas/Fort Worth airport (DFW). The TMA is a time-based strategic planning tool that assists Traffic Management Coordinators (TMCs) and En Route Air Traffic Controllers in efficiently balancing arrival demand with airport capacity. The primary algorithm in the TMA is a real-time scheduler which generates efficient landing sequences and landing times for arrivals within about 200 no a. from touchdown. This scheduler will sequence aircraft so that they arrive in a first- come - first-served (FCFS) order. While FCFS sequencing establishes a fair order based on estimated times of arrival, it does not take into account individual airline priorities among incoming flights. NASA is exploring the possibility of allowing airlines to express relative arrival priorities to air traffic management through the development of new CTAS scheduling algorithms which take into consideration airline arrival preferences. The accommodation of airline priorities in arrival sequencing and scheduling would under most circumstances result in a deviation from a "natural" or FCFS arrival order. As a First step toward developing airline influenced sequencing algorithms, an investigation was conducted to determine the feasibility of reordering arrival traffic from a strict FCFS sequence. A fast-time simulation has been developed which allows statistical evaluation of sequencing and scheduling algorithms for arrival traffic at the Dallas/Fort Worth Airport. In contrast to real-time simulation or field tests, which would require on the order of ninety minutes to examine a single traffic rush period, the fast-time simulation allows examination of multiple rush periods in a matter of seconds.

Carr, Greg↗

Airborne Management of Traffic Conflicts in Descent With Arrival Constraints

NASA is studying far-term air traffic management concepts that may increase operational efficiency through a redistribution of decisionmaking authority among airborne and ground-based elements of the air transportation system. One component of this research, En Route Free Maneuvering, allows trained pilots of equipped autonomous aircraft to assume responsibility for traffic separation. Ground-based air traffic controllers would continue to separate traffic unequipped for autonomous operations and would issue flow management constraints to all aircraft. To evaluate En Route Free Maneuvering operations, a human-in-the-loop experiment was jointly conducted by the NASA Ames and Langley Research Centers. In this experiment, test subject pilots used desktop flight simulators to resolve conflicts in cruise and descent, and to adhere to air traffic flow constraints issued by test subject controllers. Simulators at NASA Langley were equipped with a prototype Autonomous Operations Planner (AOP) flight deck toolset to assist pilots with conflict management and constraint compliance tasks. Results from the experiment are presented, focusing specifically on operations during the initial descent into the terminal area. Airborne conflict resolution performance in descent, conformance to traffic flow management constraints, and the effects of conflicting traffic on constraint conformance are all presented. Subjective data from subject pilots are also presented, showing perceived levels of workload, safety, and acceptability of autonomous arrival operations. Finally, potential AOP functionality enhancements are discussed along with suggestions to improve arrival procedures.

Doble, Nathan A.↗

Hybrid Verification of an Air Traffic Operational Concept

A concept of operations for air traffic management consists of a set of flight rules and procedures aimed to keep aircraft safely separated. This paper reports on the formal verification of separation properties of the NASA's Small Aircraft Transportation System, Higher Volume Operations (SATS HVO) concept for non-towered, non-radar airports. Based on a geometric description of the SATS HVO air space, we derive analytical formulas to compute spacing requirements on nominal approaches. Then, we model the operational concept by a hybrid non-deterministic asynchronous state transition system. Using an explicit state exploration technique, we show that the spacing requirements are always satisfied on nominal approaches. All the mathematical development presented in this paper has been formally verified in the Prototype Verification System (PVS). Keywords. Formal verification, hybrid systems, air traffic management, theorem proving

Munoz, Cesar A.↗

An Overview of Current Capabilities and Research Activities in the Airspace Operations Laboratory at NASA Ames Research Center

The Airspace Operations Laboratory at NASA Ames conducts research to provide a better understanding of roles, responsibilities, and requirements for human operators and automation in future air traffic management (ATM) systems. The research encompasses developing, evaluating, and integrating operational concepts and technologies for near-, mid-, and far-term air traffic operations. Current research threads include efficient arrival operations, function allocation in separation assurance and efficient airspace and trajectory management. The AOL has developed powerful air traffic simulation capabilities, most notably the Multi Aircraft Control System (MACS) that is used for many air traffic control simulations at NASA and its partners in government, academia and industry. Several additional NASA technologies have been integrated with the AOL's primary simulation capabilities where appropriate. Using this environment, large and small-scale system-level evaluations can be conducted to help make near-term improvements and transition NASA technologies to the FAA, such as the technologies developed under NASA's Air Traffic Management Demonstration-1 (ATD-1). The AOL's rapid prototyping and flexible simulation capabilities have proven a highly effective environment to progress the initiation of trajectory-based operations and support the mid-term implementation of NextGen. Fundamental questions about accuracy requirements have been investigated as well as realworld problems on how to improve operations in some of the most complex airspaces in the US. This includes using advanced trajectory-based operations and prototype tools for coordinating arrivals to converging runways at Newark airport and coordinating departures and arrivals in the San Francisco and the New York metro areas. Looking beyond NextGen, the AOL has started exploring hybrid human/automation control strategies as well as highly autonomous operations in the air traffic control domain. Initial results indicate improved capacity, low operator workload, good situation awareness and acceptability for controllers teaming with autonomous air traffic systems. While much research and development needs to be conducted to make such concepts a reality, these approaches have the potential to truly transform the airspace system towards increased mobility, safe and efficient growth in global operations and enabling many of the new vehicles and operations that are expected over the next decades. This paper describes how the AOL currently contributes to the ongoing air transportation transformation.

simulation↗

Quantifying the Effects of Departure and Flight Time Uncertainty on Urban Air Mobility Operations

Demand capacity balancing is a key mechanism for maintaining safe and efficient Urban Air Mobility (UAM) operations. However, uncertainties such as departure delays and flight time variation may reduce the effectiveness of algorithms used for balancing and detrimentally impact the safety and efficiency of UAM operations. In this paper, the effects of these uncertainties on UAM operations are quantified by modeling a distribution of departure and flight time errors. A route network in the Dallas/Fort Worth metropolitan area was used to simulate traffic demand with and without uncertainty. Simulations were conducted with three main models of uncertainty – first uncertainty in departure time delay resulting in late takeoffs, second with uncertainty in flight times in addition to departure delays, and finally, uncertainty in departure times that cause either late or early takeoffs. Each of these simulations were performed using varied standard deviations to fully understand the effects of uncertainties. Results from these simulations were compared to a baseline simulation using the same parameters, but without any uncertainty. The results suggest that both safety and efficiency are significantly impacted by uncertainty even with relatively low uncertainty introduced. These results work towards quantifying the effects of uncertainty in flight scheduling for UAM. They will also aid in the further development of the demand capacity balancing algorithms for UAM operations and associated air traffic management.

Urban Air Mobility↗

2022 Spring Internship Exit Presentation

As efforts of the National Aeronautics and Space Administration (NASA) and the Federal Aviation Administration (FAA) continue to digitize the air traffic management (ATM) domain, there is countless times of need for downstream natural language processing (NLP) tasks such as named entity recognition, text summarization, classification, and more. Although there are a plethora of open-sourced pre-trained transformer models in the NLP field such as BERT, RoBERTa, XLNet, and GPT-3, these models are trained on general corpora and perform poorly on domain-specific terminology and phraseology seen in ATM documents such as Notice to Airmen (NOTAMs) and Letters of Agreement (LoA). Our proposed research objective will be to first gather a large corpus of air traffic management related documents, orders, notices, books, technical papers, conference papers, articles, and other miscellaneous sources of text data from the FAA, NASA, and accredited conference and publication societies. After gathering this data, many steps will have to be taken to collate and preprocess the data into a format understandable by our test transformer models. Thirdly, we will set up training pipelines to train the RoBERTa model on its unsupervised training task masked language modelling (MLM) using resources provided by the NASA Advanced Supercomputing (NAS) facilities. Finally, these fine-tuned transformer models will be evaluated on their performance on down-stream NLP tasks as mentioned above, to show whether they will be effective when working with ATM related data or not. Once complete, this model could be made open-sourced on the HuggingFace website, where the rest of the ATM community can access and utilize this tool.

NLP↗

Exploring Human Factors Issues for Urban Air Mobility Operations

Urban air mobility (UAM) is currently receiving increased attention in the aviation literature as a new entrant into the airspace. Although the introduction of UAM offers the potential for significant benefits, it also creates the potential for fundamental change to the current air traffic management system. Several concepts are being explored to enable the development of a safe and efficient UAM system for near, mid and far term operations. A concept of operations for near term operations proposes several assumptions. Concepts for roles and responsibilities of human operators such as air traffic controllers propose different degrees of involvement. Identifying and exploring human factors issues is therefore a critical next step in the forward progression of concept development. A human-in-the-loop air traffic control simulation was used to investigate the effect of UAM traffic density and changes in current airspace routes and communication procedures on subjective controller workload and efficiency-related task performance. Findings indicate that although subjective workload was manageable for low density operations, medium and high density operations led to unmanageable levels of workload, leading to refusals to allow more vehicles into controlled airspace. By implementing a letter of agreement, verbal communications were reduced which were associated with reduced workload. Optimized routes were also associated with reduced workload and increased performance efficiency. Although these adjustments can positively support controller performance, workload still remained high during the high density UAM traffic scenarios. It is therefore suggested that, in order for UAM operation to become scalable, human operators will be required to work differently compared to current air traffic controllers. Future research should focus on the level and type of human operator or controller involvement and mated systems, to ensure safety and efficiency within UAM operations.

Air Traffic Management↗

State-Based Implicit Coordination and Applications

In air traffic management, pairwise coordination is the ability to achieve separation requirements when conflicting aircraft simultaneously maneuver to solve a conflict. Resolution algorithms are implicitly coordinated if they provide coordinated resolution maneuvers to conflicting aircraft when only surveillance data, e.g., position and velocity vectors, is periodically broadcast by the aircraft. This paper proposes an abstract framework for reasoning about state-based implicit coordination. The framework consists of a formalized mathematical development that enables and simplifies the design and verification of implicitly coordinated state-based resolution algorithms. The use of the framework is illustrated with several examples of algorithms and formal proofs of their coordination properties. The work presented here supports the safety case for a distributed self-separation air traffic management concept where different aircraft may use different conflict resolution algorithms and be assured that separation will be maintained.

Narkawicz, Anthony J.↗

Advancing the Standards for Unmanned Air System Communications, Navigation and Surveillance

Under NASA program NNA16BD84C, new architectures were identified and developed for supporting reliable and secure Communications, Navigation and Surveillance (CNS) needs for Unmanned Air Systems (UAS) operating in both controlled and uncontrolled airspace. An analysis of architectures for the two categories of airspace and an implementation technology readiness analysis were performed. These studies produced NASA reports that have been made available in the public domain and have been briefed in previous conferences. We now consider how the products of the study are influencing emerging directions in the aviation standards communities. The International Civil Aviation Organization (ICAO) Communications Panel (CP), Working Group I (WG-I) is currently developing a communications network architecture known as the Aeronautical Telecommunications Network with Internet Protocol Services (ATN/IPS). The target use case for this service is secure and reliable Air Traffic Management (ATM) for manned aircraft operating in controlled airspace. However, the work is more and more also considering the emerging class of airspace users known as Remotely Piloted Aircraft Systems (RPAS), which refers to certain UAS classes. In addition, two Special Committees (SCs) in the Radio Technical Commission for Aeronautics (RTCA) are developing Minimum Aviation System Performance Standards (MASPS) and Minimum Operational Performance Standards (MOPS) for UAS. RTCA SC-223 is investigating an Internet Protocol Suite (IPS) and AeroMACS aviation data link for interoperable (INTEROP) UAS communications. Meanwhile, RTCA SC-228 is working to develop Detect And Avoid (DAA) equipment and a Command and Control (C2) Data Link MOPS establishing LBand and C-Band solutions. These RTCA Special Committees along with ICAO CP WG/I are therefore overlapping in terms of the Communication, Navigation and Surveillance (CNS) alternatives they are seeking to provide for an integrated manned- and unmanned air traffic management service as well as remote pilot command and control. This paper presents UAS CNS architecture concepts developed under the NASA program that apply to all three of the aforementioned committees. It discusses the similarities and differences in the problem spaces under consideration in each committee, and considers the application of a common set of CNS alternatives that can be widely applied. As the works of these committees progress, it is clear that the overlap will need to be addressed to ensure a consistent and safe framework for worldwide aviation. In this study, we discuss similarities and differences in the various operational models and show how the CNS architectures developed under the NASA program apply.

Ponchak, Denise S.↗

Cooperative Automation Supporting Pilot-Dispatch Negotiation of Enroute Trajectory Change Requests

The advent of advanced technologies in communication, navigation, and surveillance is enabling more integration between the aircraft and the ground systems in managing air traffic operations. As a result, automation has evolved to provide the flight crew, air traffic controllers, and traffic flow managers with capabilities for collaborating on information access, analysis, and decision making. In this paper, we investigate different cooperative schemes between these agents, supported by automation, in managing dynamic trajectory changes while the flight is en route to improve flight and system performance. The analysis was conducted using an abstract cognitive tasking framework to identify trajectory change tasks independently from the agent performing them. Cooperation schemes were then derived by assessing different levels of cooperation on each task between the air and ground agents and their automation. The assessment was based on which automation-supported agent is more capable of performing the task and the expected benefit mechanisms that result from cooperating. The cooperation schemes were compared based on a qualitative, but objective, assessment of the benefits expected from cooperation.

air-ground integration↗

An analysis of landing rates and separations at the Dallas/Fort Worth International Airport

Advanced air traffic management systems such as the Center/TRACON Automation System (CTAS) should yield a wide range of benefits, including reduced aircraft delays and controller workload. To determine the traffic-flow benefits achievable from future terminal airspace automation, live radar information was used to perform an analysis of current aircraft landing rates and separations at the Dallas/Fort Worth International Airport. Separation statistics that result when controllers balance complex control procedural constraints in order to maintain high landing rates are presented. In addition, the analysis estimates the potential for airport capacity improvements by determining the unused landing opportunities that occur during rush traffic periods. Results suggest a large potential for improving the accuracy and consistency of spacing between arrivals on final approach, and they support earlier simulation findings that improved air traffic management would increase capacity and reduce delays.

Ballin, Mark G.↗

Fast Aircraft Separation Calculations for Gradient Based Optimization of Airspace Simulations

Simulations of airspace operational concepts can play a significant role in determining future paradigms that would allow for a safe increase in airspace density. In particular, airspace simulations which are capable of handling large numbers of aircraft act as an enabling capability for the testing of proposed airspace operational concepts. Simulations allowing for gradient based optimization methods are particularly attractive, since they would potentially allow for an efficient and empirical means to derive best operational practices. These could also allow for vehicle multidisciplinary design and optimization studies to include air traffic management considerations as a discipline. But any large scale simulation of airspace operations must include some methodology for addressing airspace separation requirements, which in the most direct sense would be tracked in a manner that computationally grows as a quadratic function of the number of simulated aircraft. Efficient indirect methods have been developed in certain contexts to address this limitation. However, any means of addressing separation requirements in a gradient based optimization context should be implemented by functions which provide analytic derivative information to maximize numerical precision and computational efficiency. In this paper, a fast and differentiable separation metric is described in application to gradient based optimization of airspace operations. Rather than computing the separation distance between every pair of aircraft in a simulation, this method effectively reduces the problem to a smaller relevant set using a geometric decomposition. This method guarantees that the smallest distance at all points in simulated time is determined exactly. When used in an optimization constraint context, this guarantees that a minimum separation is maintained between all pairs of aircraft. The presented metric has logarithmic computational growth with respect to the number of simulated aircraft, and is shown to perform well in a series of notional 2D airspace optimization problems when used to enforce specified airborne separation constraints. Results show that this is notably faster than a direct pairwise distance computing metric for optimizations involving both small and large numbers of aircraft, yet enforce separation requirements to the same tolerance. It is shown that this favorable scalability is an enabling capability for more sophisticated air traffic management conceptual studies.

Optimization↗

A Conceptual Design of a Departure Planner Decision Aid

Terminal area Air Traffic Management handles both arriving and departing traffic. To date, research work on terminal area operations has focused primarily on the arrival flow and typically departures are taken into account only in an approximate manner. However, arrivals and departures are highly coupled processes especially in the terminal airspace, with complex interactions and sharing of the same airport resources between arrivals and departures taking place in practically every important terminal area. Therefore, the addition of automation aids for departures, possibly in co-operation with existing arrival flow automation systems, could have a profound contribution in enhancing the overall efficiency of airport operations. This paper presents the conceptual system architecture for such an automation aid, the Departure Planner (DP). This architecture can be used as a core in the development of decision-aiding systems to assist air traffic controllers in improving the performance of departure operations and optimize runway time allocation among different operations at major congested airports. The design of such systems is expected to increase the overall efficiency of terminal area operations and yield benefits for all stakeholders involved in Air Traffic Management (ATM) operations, users as well as service providers.

Anagnostakis, Ioannis↗

Quantifying Effects of Departure and Flight Time Uncertainty on Urban Air Mobility Operations

Demand capacity balancing is a key mechanism for maintaining safe and efficient Urban Air Mobility (UAM) operations. However, uncertainties such as departure delays and flight time variation may reduce the effectiveness of algorithms used for balancing and detrimentally impact the safety and efficiency of UAM operations. In this paper, the effects of these uncertainties on UAM operations are quantified by modeling a distribution of departure and flight time errors. A route network in the Dallas/Fort Worth metropolitan area was used to simulate traffic demand with and without uncertainty. Simulations were conducted with three main models of uncertainty – first uncertainty in departure time delay resulting in late takeoffs, second with uncertainty in flight times in addition to departure delays, and finally, uncertainty in departure times that cause either late or early takeoffs. Each of these simulations were performed using varied standard deviations to fully understand the effects of uncertainties. Results from these simulations were compared to a baseline simulation using the same parameters, but without any uncertainty. The results suggest that both safety and efficiency are significantly impacted by uncertainty even with relatively low uncertainty introduced. These results work towards quantifying the effects of uncertainty in flight scheduling for UAM. They will also aid in the further development of the demand capacity balancing algorithms for UAM operations and associated air traffic management.

Urban Air Mobility↗

Landing-Time-Controlled Management Of Air Traffic

Conceptual system controls aircraft with old and new guidance equipment. Report begins with overview of concept, then reviews controller-interactive simulations. Describes fuel-conservative-trajectory algorithm, based on equations of motion for controlling landing time. Finally, presents results of piloted simulations.

Erzberger, Heinz↗

Airborne Use of Traffic Intent Information in a Distributed Air-Ground Traffic Management Concept: Experiment Design and Preliminary Results

A predominant research focus in the free flight community has been on the type of information required on the flight deck to enable pilots to "autonomously" maintain separation from other aircraft. At issue are the relative utility and requirement for information exchange between aircraft regarding the current "state" and/or the "intent" of each aircraft. This paper presents the experimental design and some initial findings of an experimental research study designed to provide insight into the issue of intent information exchange in constrained en-route operations and its effect on pilot decision making and flight performance. Two operational modes for autonomous operations were compared in a piloted simulation. The tactical mode was characterized primarily by the use of state information for conflict detection and resolution and an open-loop means for the pilot to meet operational constraints. The strategic mode involved the combined use of state and intent information, provided the pilot an additional level of alerting, and allowed a closed-loop approach to meeting operational constraints. Potential operational benefits of both modes are illustrated through several scenario case studies. Subjective data results are presented that generally indicate pilot consensus in favor of the strategic mode.

Wing, David J.↗

Operational Concept for the Smart Landing Facility (SLF)

The purpose of this document is to describe an operational concept for the Smart Landing Facility (SLF). The SLF is proposed as a component of the Small Aircraft Transportation System (SATS) and is envisioned to utilize Communication, Navigation, Surveillance and Air Traffic Management (CNS/ATM) technologies to support higher-volume air traffic operations in a wider variety of weather conditions than are currently possible at airports without an Air Traffic Control Tower (ATCT) or Terminal Radar Approach Control (TRACON). In order to accomplish this, the SLF will provide aircraft sequencing and separation within its terminal airspace (the SLF traffic area) and on the airport surface. The approach taken in this report is to first define and describe the SLF environment and the type of operations and aircraft that must be supported. Services currently provided by an ATCT and TRACON are reviewed and assembled into a set of high-level operational functions. A description of the applicable CNS/ATM technologies that have been deployed in the NAS (National Airspace System) or have been demonstrated to be operationally feasible is presented. A candidate SLF system concept that employs the CNS/ATM technologies is described. This is followed by SLF operational scenarios for minimally-equipped aircraft and for aircraft fully-equipped to make full use of SLF services. An assessment is made of the SLF technology and key research issues are identified.

Thompson, S. D.↗