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NASA NTRS2016

Parametric Analysis of Surveillance Quality and Level and Quality of Intent Information and Their Impact on Conflict Detection Performance

A loss-of-separation (LOS) is said to occur when two aircraft are spatially too close to one another. A LOS is the fundamental unsafe event to be avoided in air traffic management and conflict detection (CD) is the function that attempts to predict these LOS events. In general, the effectiveness of conflict detection relates to the overall safety and performance of an air traffic management concept. An abstract, parametric analysis was conducted to investigate the impact of surveillance quality, level of intent information, and quality of intent information on conflict detection performance. The data collected in this analysis can be used to estimate the conflict detection performance under alternative future scenarios or alternative allocations of the conflict detection function, based on the quality of the surveillance and intent information under those conditions.Alternatively, this data could also be used to estimate the surveillance and intent information quality required to achieve some desired CD performance as part of the design of a new separation assurance system.

Guerreiro, Nelson M.↗
NASA NTRS1983

Impact of digital systems technology on man-vehicle systems research

The present study, based on a NASA technology assessment, examines the effect of new technologies on trends in crew-systems design and their implications from the vantage point of man-vehicle systems research. Those technologies that are most relevant to future trends in crew-systems design are considered along with problems associated with the introduction of rapidly changing technologies and systems concepts from a human-factors point of view. The technologies discussed include information processing, displays and controls, flight and propulsion control, flight and systems management, air traffic control, training and simulation, and flight and resource management. The historical evolution of cockpit systems design is used to illustrate past and possible future trends in man-vehicle systems research.

Bretoi, R. N.↗
NASA NTRS2017

MESA: Message-Based System Analysis Using Runtime Verification

In this paper, we present a novel approach and framework for run-time verication of large, safety critical messaging systems. This work was motivated by verifying the System Wide Information Management (SWIM) project of the Federal Aviation Administration (FAA). SWIM provides live air traffic, site and weather data streams for the whole National Airspace System (NAS), which can easily amount to several hundred messages per second. Such safety critical systems cannot be instrumented, therefore, verification and monitoring has to happen using a nonintrusive approach, by connecting to a variety of network interfaces. Due to a large number of potential properties to check, the verification framework needs to support efficient formulation of properties with a suitable Domain Specific Language (DSL). Our approach is to utilize a distributed system that is geared towards connectivity and scalability and interface it at the message queue level to a powerful verification engine. We implemented our approach in the tool called MESA: Message-Based System Analysis, which leverages the open source projects RACE (Runtime for Airspace Concept Evaluation) and TraceContract. RACE is a platform for instantiating and running highly concurrent and distributed systems and enables connectivity to SWIM and scalability. TraceContract is a runtime verication tool that allows for checking traces against properties specified in a powerful DSL. We applied our approach to verify a SWIM service against several requirements.We found errors such as duplicate and out-of-order messages.

Message-based System↗
NASA NTRS2019

Accrued Delay Application in Trajectory-Based Operations

The air traffic management system lacks integration among its elements often due to using inconsistent information, models, and metrics about the traffic. Transitioning to trajectory-based operations, whereby flights are managed by full trajectories in space and time, will enable more integration, with the help of increased automation. Building on trajectory-based operations, an "accrued delay" metric is proposed, which continuously measures the amount of delay that a flight has accumulated up to the current time, including delays incurred during the current flight and inherited from previous flights through the turnaround process. Through a time-based metering and scheduling example, we show how using accrued delay as a metric can help integrate the decision-making across multiple decision horizons, leading to more efficient and balanced access to airspace services. We show that when prioritizing flights that have already accrued high delay because of a constrained runway resource, significant gains are achieved in terms of reducing total delay and its variance. We studied the sensitivity of these gains to numerous factors, such as time-based versus distance-based horizons, horizon size, and errors in conformance to scheduled times.

delay; trajectory-based operations; time-based flo↗
NASA NTRS2019

Accrued Delay Application in Trajectory-Based Operations

The air traffic management system lacks integration among its elements often due to using inconsistent information, models, and metrics about the traffic. Transitioning to trajectory-based operations, whereby flights are managed by full trajectories in space and time, will enable more integration, with the help of increased automation. Building on trajectory-based operations, an "accrued delay" metric is proposed, which continuously measures the amount of delay that a flight has accumulated up to the current time, including delays incurred during the current flight and inherited from previous flights through the turnaround process. Through a time-based metering and scheduling example, we show how using accrued delay as a metric can help integrate the decision-making across multiple decision horizons, leading to more efficient and balanced access to airspace services. We show that when prioritizing flights that have already accrued high delay because of a constrained runway resource, significant gains are achieved in terms of reducing total delay and its variance. We studied the sensitivity of these gains to numerous factors, such as time-based versus distance-based horizons, horizon size, and errors in conformance to scheduled times.

Idris, Husni↗
NASA NTRS2000

Automated Traffic Management System and Method

A data management system and method that enables acquisition, integration, and management of real-time data generated at different rates, by multiple heterogeneous incompatible data sources. The system achieves this functionality by using an expert system to fuse data from a variety of airline, airport operations, ramp control, and air traffic control tower sources, to establish and update reference data values for every aircraft surface operation. The system may be configured as a real-time airport surface traffic management system (TMS) that electronically interconnects air traffic control, airline data, and airport operations data to facilitate information sharing and improve taxi queuing. In the TMS operational mode, empirical data shows substantial benefits in ramp operations for airlines, reducing departure taxi times by about one minute per aircraft in operational use, translating as $12 to $15 million per year savings to airlines at the Atlanta, Georgia airport. The data management system and method may also be used for scheduling the movement of multiple vehicles in other applications, such as marine vessels in harbors and ports, trucks or railroad cars in ports or shipping yards, and railroad cars in switching yards. Finally, the data management system and method may be used for managing containers at a shipping dock, stock on a factory floor or in a warehouse, or as a training tool for improving situational awareness of FAA tower controllers, ramp and airport operators, or commercial airline personnel in airfield surface operations.

Glass, Brian J.↗
NASA NTRSDate not supplied

A Human-In-The-Loop Simulation for Urban Air Mobility in the Terminal Area

In this presentation we propose a human-in-the-loop experiment to study the potential impact of human engagement in tactical mitigation of delay in terminal area air taxi operations. The air taxi operations being considered herein is an advanced air transportation concept called Urban Air Mobility (UAM). The UAM concept aims to support not only air taxi operations, but also package delivery and emergency response among other use cases. The key innovation over current air transportation lies with the introduction of autonomous aircraft and autonomous air traffic management systems. Development of the UAM system will include transitional midterm phases where some operational services will be provided by a mixture of automation and human actors. Midterm operations present a unique challenge, since the scope of responsibility of automated systems is largely undefined, suggesting the need for direct human participation with little to inform how much human intervention is necessary. Here we assume that traffic management responsibilities require coordination between human actors and automated systems and focus on arrival flows for midterm operations. In the proposed human-in-the-loop simulation, virtual UAM traffic is strategically deconflicted by a Provider of Services for UAM at departure, then tactically managed by a human at the arrival facility. Generated traffic consists of UAM participants flying in UAM exclusive airspace structures, thus isolated from traditional traffic. The human operator is tasked with managing spacing of arrival traffic and executing speed adjustments as deemed necessary. We propose the investigation of three levels of automation assistance: 1) no assistance; 2) spacing violation detection; 3) spacing violation detection and speed adjustment recommendations. Quantitative measures like throughput and delay are used to assess the human's capacity for accommodating airborne delays. Qualitative evaluations such as surveys and open-ended feedback are used to gain insight into human factors. These factors could introduce additional capacity constraints on traffic, independent of physical or technical constraints. Although findings for this study will not be reported as the study has not yet been executed, we conclude with potential outcomes informed by previous simulations in the literature and suggestions for the structure and procedures of midterm human-automation air traffic management.

UAM↗
NASA NTRSDate not supplied

A Human-In-The-Loop Simulation for Urban Air Mobility in the Terminal Area

In this paper researchers propose a human-in-the-loop experiment to study human performance when tasked with tactical deconfliction in terminal area air taxi operations. The air taxi operations being considered herein are an advanced air transportation concept called Urban Air Mobility (UAM). The UAM concept aims to support not only air taxi operations, but also package delivery and emergency response among other use cases. The key innovation over current air transportation lies with the introduction of highly automated aircraft and air traffic management systems. Development of the UAM system will include transitional midterm phases where some operational services will be provided by a mixture of automation and human actors. Midterm operations present a unique challenge, since the scope of responsibility of automated systems is largely undefined, suggesting the need for direct human participation with little to inform how much human intervention is necessary. Here it is assumed that traffic management responsibilities require coordination between human actors and automated systems and focus on arrival flows for midterm operations. In the proposed human-in-the-loop simulation, virtual UAM traffic is strategically deconflicted by a Provider of Services for UAM at departure, then tactically managed by a human at the arrival facility. Generated traffic consists of UAM participants flying in UAM exclusive airspace structures, thus isolated from traditional traffic. The human operator is tasked with managing spacing of arrival traffic and executing speed adjustments as deemed necessary. Researchers propose the investigation of three levels of automation assistance: 1) no assistance; 2) spacing violation detection; 3) spacing violation detection and speed adjustment recommendations. Quantitative measures like throughput and delay are used to assess the human's capacity for accommodating airborne delays. Qualitative evaluations such as surveys and open-ended feedback are used to gain insight into human factors. These factors could introduce additional capacity constraints on traffic, independent of physical or technical constraints. Although findings for this study will not be reported as the study has not yet been executed, the authors conclude with potential outcomes informed by previous simulations in the literature and suggestions for the structure and procedures of midterm human-automation air traffic management.

UAM↗
NASA NTRS2016

An Integrated Gate Turnaround Management Concept Leveraging Big Data Analytics for NAS Performance Improvements

"Gate Turnaround" plays a key role in the National Air Space (NAS) gate-to-gate performance by receiving aircraft when they reach their destination airport, and delivering aircraft into the NAS upon departing from the gate and subsequent takeoff. The time spent at the gate in meeting the planned departure time is influenced by many factors and often with considerable uncertainties. Uncertainties such as weather, early or late arrivals, disembarking and boarding passengers, unloading/reloading cargo, aircraft logistics/maintenance services and ground handling, traffic in ramp and movement areas for taxi-in and taxi-out, and departure queue management for takeoff are likely encountered on the daily basis. The Integrated Gate Turnaround Management (IGTM) concept is leveraging relevant historical data to support optimization of the gate operations, which include arrival, at the gate, departure based on constraints (e.g., available gates at the arrival, ground crew and equipment for the gate turnaround, and over capacity demand upon departure), and collaborative decision-making. The IGTM concept provides effective information services and decision tools to the stakeholders, such as airline dispatchers, gate agents, airport operators, ramp controllers, and air traffic control (ATC) traffic managers and ground controllers to mitigate uncertainties arising from both nominal and off-nominal airport gate operations. IGTM will provide NAS stakeholders customized decision making tools through a User Interface (UI) by leveraging historical data (Big Data), net-enabled Air Traffic Management (ATM) live data, and analytics according to dependencies among NAS parameters for the stakeholders to manage and optimize the NAS performance in the gate turnaround domain. The application will give stakeholders predictable results based on the past and current NAS performance according to selected decision trees through the UI. The predictable results are generated based on analysis of the unique airport attributes (e.g., runway, taxiway, terminal, and gate configurations and tenants), and combined statistics from past data and live data based on a specific set of ATM concept-of-operations (ConOps) and operational parameters via systems analysis using an analytic network learning model. The IGTM tool will then bound the uncertainties that arise from nominal and off-nominal operational conditions with direct assessment of the gate turnaround status and the impact of a certain operational decision on the NAS performance, and provide a set of recommended actions to optimize the NAS performance by allowing stakeholders to take mitigation actions to reduce uncertainty and time deviation of planned operational events. An IGTM prototype was developed at NASA Ames Simulation Laboratories (SimLabs) to demonstrate the benefits and applicability of the concept. A data network, using the System Wide Information Management (SWIM)-like messaging application using the ActiveMQ message service, was connected to the simulated data warehouse, scheduled flight plans, a fast-time airport simulator, and a graphic UI. A fast-time simulation was integrated with the data warehouse or Big Data/Analytics (BAI), scheduled flight plans from Aeronautical Operational Control AOC, IGTM Controller, and a UI via a SWIM-like data messaging network using the ActiveMQ message service, illustrated in Figure 1, to demonstrate selected use-cases showing the benefits of the IGTM concept on the NAS performance.

Efficent ATM systems↗
NASA NTRS2002

NASA Langley and NLR Research of Distributed Air/Ground Traffic Management

Distributed Air/Ground Traffic Management (DAG-TM) is a concept of future air traffic operations that proposes to distribute information, decision-making authority, and responsibility among flight crews, the air traffic service provider, and aeronautical operational control organizations. This paper provides an overview and status of DAG-TM research at NASA Langley Research Center and the National Aerospace Laboratory of The Netherlands. Specific objectives of the research are to evaluate the technical and operational feasibility of the autonomous airborne component of DAG-TM, which is founded on the operational paradigm of free flight. The paper includes an overview of research approaches, the airborne technologies under development, and a summary of experimental investigations and findings to date. Although research is not yet complete, these findings indicate that free flight is feasible and will significantly enhance system capacity and safety. While free flight cannot alone resolve the complex issues faced by those modernizing the global airspace, it should be considered an essential part of a comprehensive air traffic management modernization activity.

Ballin, Mark G.↗
NASA NTRS2012

UAS Integration Into the NAS: An Examination of Baseline Compliance in the Current Airspace System

As a result of the FAA Modernization and Reform Act of 2012, Unmanned Aerial Systems (UAS) are expected to be integrated into the National Airspace System (NAS) by 2015. Several human factors challenges need to be addressed before UAS can safely and routinely fly in the NAS with manned aircraft. Perhaps the most significant challenge is for the UAS to be non-disruptive to the air traffic management system. Another human factors challenge is how to provide UAS pilots with intuitive traffic information in order to support situation awareness (SA) of their airspace environment as well as a see-and-avoid capability comparable to manned aircraft so that a UAS pilot could safely maneuver the aircraft to maintain separation and collision avoidance if necessary. A simulation experiment was conducted to examine baseline compliance of UAS operations in the current airspace system. Researchers also examined the effects of introducing a Cockpit Situation Display (CSD) into a UAS Ground Control Station (GCS) on UAS pilot performance, workload and situation awareness while flying in a positively controlled sector. Pilots were tasked with conducting a highway patrol police mission with a Medium Altitude Long Endurance (MALE) UAS in L.A. Center airspace with two mission objectives: 1) to reroute the UAS when issued new instructions from their commander, and 2) to communicate with Air Traffic Control (ATC) to negotiate flight plan changes and respond to vectoring and altitude change instructions. Objective aircraft separation data, workload ratings, SA data, and subjective ratings regarding UAS operations in the NAS were collected. Results indicate that UAS pilots were able to comply appropriately with ATC instructions. In addition, the introduction of the CSD improved pilot SA and reduced workload associated with UAS and ATC interactions.

Fern, Lisa↗
NASA NTRS2012

Intuitiveness of Symbol Features for Air Traffic Management

We present the results of two online surveys asking participants to indicate what type of air traffic information might be conveyed by a number of symbols and symbol features (color, fill, text, and shape). The results of this initial study suggest that the well-developed concepts of ownership, altitude, and trajectory are readily associated with certain symbol features, while the relatively novel concept of equipage was not clearly associated with any specific symbol feature.

Ngo, Mary Kim↗
NASA NTRS2005

Towards a Functionally-Formed Air Traffic System-of-Systems

Incremental improvements to the national aviation infrastructure have not resulted in sufficient increases in capacity and flexibility to meet emerging demand. Unfortunately, revolutionary changes capable of substantial and rapid increases in capacity have proven elusive. Moreover, significant changes have been difficult to implement, and the operational consequences of such change, difficult to predict due to the system s complexity. Some research suggests redistributing air traffic control functions through the system, but this work has largely been dismissed out of hand, accused of being impractical. However, the case for functionally-based reorganization of form can be made from a theoretical, systems perspective. This paper investigates Air Traffic Management functions and their intrinsic biases towards centralized/distributed operations, grounded in systems engineering and information technology theories. Application of these concepts to a small airport operations design is discussed. From this groundwork, a robust, scalable system transformation plan may be made in light of uncertain demand.

Conway, Sheila R.↗
NASA NTRS1998

Shared Situation Awareness in the Flight Deck-ATC System

New technologies and operational concept changes have been proposed for implementation in the National Airspace System (NAS). These changes include improved datalink (CPDLC) technologies for providing improved weather, traffic, Flight Object (FO) and navigation information to the pilot and controller, and new forms of automation for both the flight deck and air traffic management system. In addition, the way business is conducted in the NAS is under consideration. Increases in the discretion provided to pilots (and dispatchers in commercial airlines) are being contemplated in an effort to increase system capacity and flexibility. New concepts of operation (e.g., Collaborative Decision Making and Free Flight) allow for more control to be given to the cockpit or airline with correspondingly greater monitoring responsibilities on the ground. In addition, new technologies and displays make possible much greater information flow between the ground and the cockpit and also dramatic changes in the type of information provided. Designing to support these changes suggests two integrally linked questions: (1) What display technologies and information are needed to support desired changes responsibilities? (2) How will the changes in information availability influence the negotiation process between the cockpit and the ground? Each of these proposed changes (both in technology and operational concept) will have a marked impact on the performance, workload, and Situation Awareness (SA) of both pilots and controllers. Typically such changes are evaluated independently in terms of the effects of the proposed change on either pilot performance or ATC performance. It is proposed here, however, that in order to fully understand the effects of such changes, the joint pilot/controller system must be considered.

Endsley, Mica R.↗
NASA NTRSDate not supplied

Real World Applications of AI/ML in Optimizing Airspace Operations

As National Airspace System (NAS) is going through the Digital Transformation journey, data science and analytics methods can significantly contribute to improving the traditional physics-based decision-making tools. The adoption of AI/ML methods will not only help accelerate Federal Aviation Administration (FAA)’s vision of Info-centric NAS but also contribute to the overall objective of sustainable aviation. AI/ML can improve the ground and airspace operations by enhancing the accuracy of current decision-making tools used by the airlines and the FAA to manage traffic on the ground and in the air. Huge amount of data that gets collected during a flight. AI/ML methods can extract information from this data and provide valuable insights to make better operational decisions. NASA has partnered with the FAA and commercial airlines such as American and Southwest Airlines on this effort and has successfully demonstrated the benefits of using ML in real world environment by reducing delays and optimizing ground operations at the US airports. In 2022 itself, NASA demonstrated real-world benefits (over 24K lbs. of fuel savings, over 76.6K lbs. CO2 emission savings, and several hours of delay savings) by deploying ML based prediction models to optimize ground operations at Dallas/Fort Worth International and Dallas Love Field Airports in Texas. These tools are being deployed on the cloud for broader deployment, adaptability, and scalability. NASA is developed a reference implementation of the cloud-based platform to significantly lower the bar to development and distribution of these digital services for aviation. In this talk, I will share information about the Digital Information Platform project, the novel AI/ML based approaches used for optimizing ground operations and the opportunities to partner with NASA on these demonstrations.

air traffic management↗
NASA NTRS2011

Evaluation of the Monotonic Lagrangian Grid and Lat-Long Grid for Air Traffic Management

The Air Traffic Monotonic Lagrangian Grid (ATMLG) is used to simulate a 24 hour period of air traffic flow in the National Airspace System (NAS). During this time period, there are 41,594 flights over the United States, and the flight plan information (departure and arrival airports and times, and waypoints along the way) are obtained from an Federal Aviation Administration (FAA) Enhanced Traffic Management System (ETMS) dataset. Two simulation procedures are tested and compared: one based on the Monotonic Lagrangian Grid (MLG), and the other based on the stationary Latitude-Longitude (Lat- Long) grid. Simulating one full day of air traffic over the United States required the following amounts of CPU time on a single processor of an SGI Altix: 88 s for the MLG method, and 163 s for the Lat-Long grid method. We present a discussion of the amount of CPU time required for each of the simulation processes (updating aircraft trajectories, sorting, conflict detection and resolution, etc.), and show that the main advantage of the MLG method is that it is a general sorting algorithm that can sort on multiple properties. We discuss how many MLG neighbors must be considered in the separation assurance procedure in order to ensure a five-mile separation buffer between aircraft, and we investigate the effect of removing waypoints from aircraft trajectories. When aircraft choose their own trajectory, there are more flights with shorter duration times and fewer CD&R maneuvers, resulting in significant fuel savings.

Kaplan, Carolyn↗
NASA NTRS2001

Real-Time Surface Traffic Adviser

A real-time data management system which uses data generated at different rates by multiple heterogeneous incompatible data sources are presented. In one embodiment, the invention is as an airport surface traffic data management system (traffic adviser) that electronically interconnects air traffic control, airline, and airport operations user communities to facilitate information sharing and improve taxi queuing. The system uses an expert system to fuse dam from a variety of airline, airport operations, ramp control, and air traffic control sources, in order to establish, predict, and update reference data values for every aircraft surface operation.

Brian J Glass↗