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NASA NTRS2005

An Initial Study of Airport Arrival Heinz Capacity Benefits Due to Improved Scheduling Accuracy

The long-term growth rate in air-traffic demand leads to future air-traffic densities that are unmanageable by today's air-traffic control system. I n order to accommodate such growth, new technology and operational methods will be needed in the next generation air-traffic control system. One proposal for such a system is the Automated Airspace Concept (AAC). One of the precepts of AAC is to direct aircraft using trajectories that are sent via an air-ground data link. This greatly improves the accuracy in directing aircraft to specific waypoints at specific times. Studies of the Center-TRACON Automation System (CTAS) have shown that increased scheduling accuracy enables increased arrival capacity at CTAS equipped airports.

Meyn, Larry↗

NASA NTRS2010

Accelerated Monte Carlo Simulation for Safety Analysis of the Advanced Airspace Concept

Safe separation of aircraft is a primary objective of any air traffic control system. An accelerated Monte Carlo approach was developed to assess the level of safety provided by a proposed next-generation air traffic control system. It combines features of fault tree and standard Monte Carlo methods. It runs more than one order of magnitude faster than the standard Monte Carlo method while providing risk estimates that only differ by about 10%. It also preserves component-level model fidelity that is difficult to maintain using the standard fault tree method. This balance of speed and fidelity allows sensitivity analysis to be completed in days instead of weeks or months with the standard Monte Carlo method. Results indicate that risk estimates are sensitive to transponder, pilot visual avoidance, and conflict detection failure probabilities.

Thipphavong, David↗

NASA NTRS2017

Enabling Airspace Integration for High Density Urban Air Mobility

Aviation technologies and concepts have reached a level of maturity that may soon enable an era of on-demand mobility (ODM) fueled by quiet, efficient, and largely automated air taxis. However, successfully bringing such a system to fruition will require introducing orders of magnitude more aircraft to a given airspace volume than can be accommodated by the traditional air traffic control system, among other important technical challenges. The airspace integration problem is further compounded by requirements to set aside appropriate ground infrastructure for take-off and landing areas and ensuring these new aircraft types and their operations do not burden traditional airspace users and air traffic control. These challenge for ODM may be significantly reduced by extending the concepts and technologies developed to manage small unmanned aircraft systems (UAS) at low altitude the UAS traffic management (UTM) system to higher altitudes and aircraft with humans onboard in controlled airspace, or by equipping ODM aircraft with advanced sensors, algorithms, and interfaces. The precedent of operational freedom inherent in visual flight rules and the technologies developed for large UAS and commercial aircraft automation will contribute to the evolution of an ODM system enabled by UTM. This paper describes the set of air traffic services, normally provided by the traditional air traffic system, that an ODM system would implement to achieve the high densities needed for ODMs economic viability. Finally, the paper proposes a framework for integrating, evaluating, and deploying low-, medium-, and high-density ODM concepts that build on each other to ensure operational and economic feasibility at every step.

Mueller, Eric Richard↗

NASA NTRS2018

Enabling Airspace Integration for High Density Urban Air Mobility Operations

Aviation technologies and concepts have reached a level of maturity that may soon enable an era of on-demand mobility (ODM) fueled by quiet, efficient, and largely automated air taxis. However, successfully bringing such a system to fruition will require introducing orders-of-magnitude more aircraft to a given airspace volume than can be accommodated by the traditional air traffic control system, among other important technical challenges. The airspace integration problem is further compounded by requirements to set aside appropriate ground infrastructure for take-off and landing areas and ensuring these new aircraft types and their operations do not overly burden traditional airspace users and air traffic control. These challenges for ODM may be significantly reduced by extending the concepts and technologies developed to manage small unmanned aircraft systems (UAS) at low altitude "the UAS traffic management (UTM) system" to higher altitudes and aircraft with humans onboard in controlled airspace, or by equipping ODM aircraft with advanced sensors, algorithms, and interfaces. The precedent of operational freedom inherent in visual flight rules and the technologies developed for large UAS and commercial aircraft automation will contribute to the evolution of an ODM system enabled by UTM. This paper describes the set of air traffic services, normally provided by the traditional air traffic system, that an ODM system would implement to achieve the high densities needed for ODM's economic viability. Finally, the paper proposes a framework for integrating, evaluating, and deploying low-, medium-, and high-density ODM concepts that build on each other to ensure operational and economic feasibility at every step.

Mueller, Eric↗

NASA NTRSDate not supplied

Design and Analysis of Corridors for UAM Operations

Urban Air Mobility (UAM) is predicted to provide alternate modes of transportation for cargo and passengers in the urban areas. Integration of UAM operations into the National Airspace System is a challenge especially around large airport. The Federal Aviation Administration’s (FAA) UAM Concept of Operations (ConOps) suggests new airspace structures for UAM operations such as corridors where FAA air traffic control (ATC) will not be expected to provide services. This paper presents a design for corridors in the Dallas Fort Worth (DFW) area that attempts to minimize air traffic controller interactions with UAM pilots and operators. The corridor and vertiports are then analyzed with respect to Class B separation criteria and wake advisory criteria. The results show that for the corridors designed for the DFW area and presented in this research, in some cases Class B separation criteria are not available between UAM corridors and legacy traffic due to the geometry of the airport. It shows that wake advisory criteria were not met for some segments in North Flow traffic but were generally met in South Flow. This means that some corridor segments at DFW airport will not be available for a given airport flow and may need new placements, which need further investigation.

Urban Air Mobility↗

NASA NTRS2020

Analysis of Pilot Monitoring Skills and a Review of Training Effectiveness

The commercial aviation industry world-wide has identified a need for improved pilot monitoring and awareness (e.g., FAA, 2013, ICAO, 2016). More specifically, aviation safety data indicate that failures in pilots’ flight path management (FPM) monitoring and awareness have contributed to a range of undesired outcomes: accidents, major upsets, and non-compliance with air traffic control (ATC) guidance. The Federal Aviation Administration (FAA) has further stated that these types of FPM failures are likely to worsen with the increasingly complex air traffic control systems and FPM concepts proposed for NextGen (https://www.faa. gov/nextgen/what_is_nextgen/) operations (e.g., see Hah et al., 2017). Adding to this complexity is the introduction of increasingly automated aircraft systems that can increase monitoring burdens. One potential mitigation for this situation is to enhance pilot training for effective monitoring. NASA Ames Research Center was asked to identify and evaluate training approaches that have the potential to enhance pilots’ ability to effectively monitor for FPM (with the result of improved awareness). The focus of this work is to identify, develop or validate training guidance to improve pilot monitoring/awareness regarding FPM and mitigate the recent trend of accidents and incidents, especially loss of control (LOC) events. The result of this work should be input for improved industry standards and FAA guidance to reduce the risk of incidents and accidents due to inadequate pilot monitoring/awareness. This is the first of three reports that were developed for this project.

aviation human factors↗

NASA NTRS2011

Trajectory Assessment and Modification Tools for Next Generation Air Traffic Management Operations

This paper reviews three Next Generation Air Transportation System (NextGen) based high fidelity air traffic control human-in-the-loop (HITL) simulations, with a focus on the expected requirement of enhanced automated trajectory assessment and modification tools to support future air traffic flow management (ATFM) planning positions. The simulations were conducted at the National Aeronautics and Space Administration (NASA) Ames Research Centers Airspace Operations Laboratory (AOL) in 2009 and 2010. The test airspace for all three simulations assumed the mid-term NextGenEn-Route high altitude environment utilizing high altitude sectors from the Kansas City and Memphis Air Route Traffic Control Centers. Trajectory assessment, modification and coordination decision support tools were developed at the AOL in order to perform future ATFM tasks. Overall tool usage results and user acceptability ratings were collected across three areas of NextGen operatoins to evaluate the tools. In addition to the usefulness and usability feedback, feasibility issues, benefits, and future requirements were also addressed. Overall, the tool sets were rated very useful and usable, and many elements of the tools received high scores and were used frequently and successfully. Tool utilization results in all three HITLs showed both user and system benefits including better airspace throughput, reduced controller workload, and highly effective communication protocols in both full Data Comm and mixed-equipage environments.

Brasil, Connie↗

NASA NTRS1997

Identification of Error Patterns in Terminal-Area ATC Communications

Advancing air traffic management technologies have enabled a greater number of aircraft to use the same airspace more effectively. As aircraft separations are reduced and final approaches are more finely timed, there is less room for error. The present study examined 122 terminal-area, loss-of-separation and procedure violation incidents reported to the Aviation Safety Reporting System (ASRS) by air traffic controllers. Narrative description codes were used for the incidents for type of violation, contributing factors, recovery strategies, and consequences. Usually multiple errors occurred prior to the violation. Error sequences were analyzed and common patterns of errors were identified. In half of the incidents, errors were noticed in time to correct mistakes. Of these, almost 43% committed additional errors during the recovery attempt. This analysis shows that redundancies in the present air traffic control system may not be sufficient to support large increases in traffic density. Error prevention and design considerations for air traffic management systems are discussed.

Quinn, Cheryl↗

NASA NTRS2010

Analysis of Different Cost Functions in the Geosect Airspace Partitioning Tool

A new cost function representing air traffic controller workload is implemented in the Geosect airspace partitioning tool. Geosect currently uses a combination of aircraft count and dwell time to select optimal airspace partitions that balance controller workload. This is referred to as the aircraft count/dwell time hybrid cost function. The new cost function is based on Simplified Dynamic Density, a measure of different aspects of air traffic controller workload. Three sectorizations are compared. These are the current sectorization, Geosect's sectorization based on the aircraft count/dwell time hybrid cost function, and Geosect s sectorization based on the Simplified Dynamic Density cost function. Each sectorization is evaluated for maximum and average workload along with workload balance using the Simplified Dynamic Density as the workload measure. In addition, the Airspace Concept Evaluation System, a nationwide air traffic simulator, is used to determine the capacity and delay incurred by each sectorization. The sectorization resulting from the Simplified Dynamic Density cost function had a lower maximum workload measure than the other sectorizations, and the sectorization based on the combination of aircraft count and dwell time did a better job of balancing workload and balancing capacity. However, the current sectorization had the lowest average workload, highest sector capacity, and the least system delay.

Wong, Gregory L.↗

NASA NTRS2019

Evaluation of Technology Concepts for Traffic Data Management and Relevant Audio for Datalink in Commercial Airline Flight Decks

Datalink is currently operational for departure clearances and in oceanic environments and is currently being tested in high altitude domestic enroute airspace. Interaction with even simple datalink clearances may create more workload for flight crews than the voice system they replace if not carefully designed. Datalink may also introduce additional complexity for flight crews with hundreds of uplink messages now defined for use. Finally, flight crews may lose airspace awareness and operationally relevant information that they normally pickup from Air Traffic Control (ATC) voice communications with other aircraft (i.e., “party-line” transmissions). Once again, automation may be poised to increase workload on the flight deck for incremental benefit. Datalink implementation to support future air traffic management concepts needs to be carefully considered, understanding human communication norms and especially, the change from voice- to text-based communications modality and its effect on pilot workload and situation awareness. Increasingly autonomous systems, where autonomy is designed to support human-autonomy teaming, may be suited to solve these issues. NASA is conducting research and development of increasingly autonomous systems, utilizing machine-learning algorithms seamlessly integrated with humans whereby task performance of the combined system is significantly greater than the individual components. Increasingly autonomous systems offer the potential for significantly improved levels of performance and safety that are superior to either human or automation alone. Two increasingly autonomous systems concepts - a traffic data manager and a conversational co-pilot - were developed to intelligently address the datalink issues in a complex, future state environment with significant levels of traffic. The system was tested for suitability of datalink usage for terminal airspace. The traffic data manager allowed for automated declutter of the Automatic Dependent Surveillance-Broadcast (ADS-B) display. The system determined relevant traffic for display based on machine learning algorithms trained by experienced human pilot behaviors. The conversational co-pilot provided relevant audio air traffic control messages based on context and proximity to ownship. Both systems made use of the connected aircraft concepts to provide intelligent context to determine relevancy above and beyond proximity to ownship. A human-in-the-loop test was conducted in NASA Langley Research Center’s Integration Flight Deck B-737-800 simulator to evaluate the traffic data manager and the conversational co-pilot. Twelve airline crews flew various normal and non-normal procedures and their actions and performance were recorded in response to the procedural events. This paper details the flight crew performance and evaluation during the events.

Etherington, Timothy↗

NASA NTRS2015

NASA Controller Acceptability Study 1(CAS-1) Experiment Description and Initial Observations

This paper describes the Controller Acceptability Study 1 (CAS-1) experiment that was conducted by NASA Langley Research Center personnel from January through March 2014 and presents partial CAS-1 results. CAS-1 employed 14 air traffic controller volunteers as research subjects to assess the viability of simulated future unmanned aircraft systems (UAS) operating alongside manned aircraft in moderate-density, moderate-complexity Class E airspace. These simulated UAS were equipped with a prototype pilot-in-the-loop (PITL) Detect and Avoid (DAA) system, specifically the Self-Separation (SS) function of such a system based on Stratway+ software to replace the see-and-avoid capabilities of manned aircraft pilots. A quantitative CAS-1 objective was to determine horizontal miss distance (HMD) values for SS encounters that were most acceptable to air traffic controllers, specifically HMD values that were assessed as neither unsafely small nor disruptively large. HMD values between 0.5 and 3.0 nautical miles (nmi) were assessed for a wide array of encounter geometries between UAS and manned aircraft. The paper includes brief introductory material about DAA systems and their SS functions, followed by descriptions of the CAS-1 simulation environment, prototype PITL SS capability, and experiment design, and concludes with presentation and discussion of partial CAS-1 data and results.

Chamberlain, James P.↗

NASA NTRS2011

Evaluation of High Density Air Traffic Operations with Automation for Separation Assurance, Weather Avoidance and Schedule Conformance

In this paper we discuss the development and evaluation of our prototype technologies and procedures for far-term air traffic control operations with automation for separation assurance, weather avoidance and schedule conformance. Controller-in-the-loop simulations in the Airspace Operations Laboratory at the NASA Ames Research Center in 2010 have shown very promising results. We found the operations to provide high airspace throughput, excellent efficiency and schedule conformance. The simulation also highlighted areas for improvements: Short-term conflict situations sometimes resulted in separation violations, particularly for transitioning aircraft in complex traffic flows. The combination of heavy metering and growing weather resulted in an increased number of aircraft penetrating convective weather cells. To address these shortcomings technologies and procedures have been improved and the operations are being re-evaluated with the same scenarios. In this paper we will first describe the concept and technologies for automating separation assurance, weather avoidance, and schedule conformance. Second, the results from the 2010 simulation will be reviewed. We report human-systems integration aspects, safety and efficiency results as well as airspace throughput, workload, and operational acceptability. Next, improvements will be discussed that were made to address identified shortcomings. We conclude that, with further refinements, air traffic control operations with ground-based automated separation assurance can routinely provide currently unachievable levels of traffic throughput in the en route airspace.

Prevot, Thomas↗

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 NTRS1980

An evaluation of NASA's program for improving aircraft fuel efficiency

The report provides commentary and recommendations where appropriate on each of the major elements of the program. Key findings of the committee included a recommendation that closer ties be established between NASA and the FAA to expedite the use and acceptance of the new technology. The committee also cited the potential for fuel savings through an imporved air traffic control system and recommended that the management of NASA and the FAA discuss ways and means to work together to exploit more effectively the capabilities and responsibilities of each to develop air traffic control.

Source record↗

NASA NTRS2017

Enabling Airspace Integration for High-Density On-Demand Mobility Operations

Aviation technologies and concepts have reached a level of maturity that may soon enable an era of on-demand mobility (ODM) fueled by quiet, efficient, and largely automated air taxis. However, successfully bringing such a system to fruition will require introducing orders of magnitude more aircraft to a given airspace volume than can be accommodated by the traditional air traffic control system, among other important technical challenges. The airspace integration problem is further compounded by requirements to set aside appropriate ground infrastructure for take-off and landing areas and ensuring these new aircraft types and their operations do not burden traditional airspace users and air traffic control. This airspace integration challenge may be significantly reduced by extending the concepts and technologies developed to manage small unmanned aircraft systems (UAS) at low altitudethe UAS traffic management (UTM) systemto higher altitudes and new aircraft types, or by equipping ODM aircraft with advanced sensors, algorithms, and interfaces. The precedent of operational freedom inherent in visual flight rules and the technologies developed for large UAS and commercial aircraft automation will contribute to the evolution of an ODM system enabled by UTM. This paper describes the set of air traffic services, normally provided by the traditional air traffic system, that an ODM system would implement to achieve the high densities needed for ODMs economic viability. Finally, the paper proposes a framework for integrating, evaluating, and deploying low-, medium-, and high-density ODM concepts that build on each other to ensure operational and economic feasibility at every step.

Mueller, Eric↗

NASA NTRS2017

Enabling Airspace Integration for High-Density On-Demand Mobility Operations

Aviation technologies and concepts have reached a level of maturity that may soon enable an era of on-demand mobility (ODM) fueled by quiet, efficient, and largely automated air taxis. However, successfully bringing such a system to fruition will require introducing orders of magnitude more aircraft to a given airspace volume than can be accommodated by the traditional air traffic control system, among other important technical challenges. The airspace integration problem is further compounded by requirements to set aside appropriate ground infrastructure for take-off and landing areas and ensuring these new aircraft types and their operations do not burden traditional airspace users and air traffic control. This airspace integration challenge may be significantly reduced by extending the concepts and technologies developed to manage small unmanned aircraft systems (UAS) at low altitude - the UAS traffic management (UTM) system - to higher altitudes and new aircraft types, or by equipping ODM aircraft with advanced sensors, algorithms, and interfaces. The precedent of operational freedom inherent in visual flight rules and the technologies developed for large UAS and commercial aircraft automation will contribute to the evolution of an ODM system enabled by UTM. This paper describes the set of air traffic services, normally provided by the traditional air traffic system, that an ODM system would implement to achieve the high densities needed for ODM's economic viability. Finally, the paper proposes a framework for integrating, evaluating, and deploying low-, medium-, and high-density ODM concepts that build on each other to ensure operational and economic feasibility at every step.

Mueller, Eric↗

NASA NTRS1998

A Cognitive-System Model for En Route Air Traffic Management

NASA Ames Research Center has been engaged in the development of advanced air traffic management technologies whose basic form is cognitive aiding systems for air traffic controller and flight deck operations. In the design and evaluation of such systems the dynamic interaction between the airborne aiding system and the ground-based aiding systems forms a critical coupling for control. The human operator is an integral control element in the system and the optimal integration of human decision and performance parameters with those of the automation aiding systems offers a significant challenge to cognitive engineering. This paper presents a study in full mission simulation and the development of a predictive computational model of human performance. We have found that this combination of methodologies provide a powerful design-aiding process. We have extended the computational model Man Machine Integrated Design and Analysis System (N13DAS) to include representation of multiple cognitive agents (both human operators and intelligent aiding systems), operating aircraft airline operations centers and air traffic control centers in the evolving airspace. The demands of this application require the representation of many intelligent agents sharing world-models, and coordinating action/intention with cooperative scheduling of goals and actions in a potentially unpredictable world of operations. The operator's activity structures have been developed to include prioritization and interruption of multiple parallel activities among multiple operators, to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. We have exercised this model in a multi-air traffic sector scenario with potential conflict among aircraft at and across sector boundaries. We have modeled the control situation as a multiple closed loop system. The inner and outer loop alerting structure of air traffic management has many implications that need to be investigated to assure adequate design. First, there are control and stability factors implicit in the design. As the inner loop response time approaches that of the outer loop, system stability may be compromised in that controllers may be solving a problem the nature of which has already been changed by pilot action. Second, information exchange and information presentation for both air and ground must be designed to complement as opposed to compete with each other. Third, the level of individual and shared awareness in trajectory modification and flight conformance needs to be defined. Fourth, the level of required awareness and performance impact of mixed fleet operations and failed-mode recovery must be explored.

Corker, Kevin M.↗

NASA NTRS2003

Runway Operations Planning: A Two-Stage Solution Methodology

The airport runway is a scarce resource that must be shared by different runway operations (arrivals, departures and runway crossings). Given the possible sequences of runway events, careful Runway Operations Planning (ROP) is required if runway utilization is to be maximized. Thus, Runway Operations Planning (ROP) is a critical component of airport operations planning in general and surface operations planning in particular. From the perspective of departures, ROP solutions are aircraft departure schedules developed by optimally allocating runway time for departures given the time required for arrivals and crossings. In addition to the obvious objective of maximizing throughput, other objectives, such as guaranteeing fairness and minimizing environmental impact, may be incorporated into the ROP solution subject to constraints introduced by Air Traffic Control (ATC) procedures. Generating optimal runway operations plans was approached in with a 'one-stage' optimization routine that considered all the desired objectives and constraints, and the characteristics of each aircraft (weight class, destination, Air Traffic Control (ATC) constraints) at the same time. Since, however, at any given point in time, there is less uncertainty in the predicted demand for departure resources in terms of weight class than in terms of specific aircraft, the ROP problem can be parsed into two stages. In the context of the Departure Planner (OP) research project, this paper introduces Runway Operations Planning (ROP) as part of the wider Surface Operations Optimization (SOO) and describes a proposed 'two stage' heuristic algorithm for solving the Runway Operations Planning (ROP) problem. Focus is specifically given on including runway crossings in the planning process of runway operations. In the first stage, sequences of departure class slots and runwy crossings slots are generated and ranked based on departure runway throughput under stochastic conditions. In the second stage, the departure class slots are populated with specific flights from the pool of available aircraft, by solving an integer program. Preliminary results from the algorithm implementation on real-world traffic data are included.

Anagnostakis, Ioannis↗