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NASA NTRS2011

An overview of the V&V of Flight-Critical Systems effort at NASA

As the US is getting ready for the Next Generation (NextGen) of Air Traffic System, there is a growing concern that the current techniques for verification and validation will not be adequate for the changes to come. The JPDO (in charge of implementing NextGen) has given NASA a mandate to address the problem and it resulted in the formulation of the V&V of Flight-Critical Systems effort. This research effort is divided into four themes: argument-based safety assurance, distributed systems, authority and autonomy, and, software intensive systems. This paper presents an overview of the technologies that will address the problem.

validation↗
NASA NTRS2014

Agent Based Modeling of Air Carrier Behavior for Evaluation of Technology Equipage and Adoption

As part of ongoing research, the National Aeronautics and Space Administration (NASA) and LMI developed a research framework to assist policymakers in identifying impacts on the U.S. air transportation system (ATS) of potential policies and technology related to the implementation of the Next Generation Air Transportation System (NextGen). This framework, called the Air Transportation System Evolutionary Simulation (ATS-EVOS), integrates multiple models into a single process flow to best simulate responses by U.S. commercial airlines and other ATS stakeholders to NextGen-related policies, and in turn, how those responses impact the ATS. Development of this framework required NASA and LMI to create an agent-based model of airline and passenger behavior. This Airline Evolutionary Simulation (AIRLINE-EVOS) models airline decisions about tactical airfare and schedule adjustments, and strategic decisions related to fleet assignments, market prices, and equipage. AIRLINE-EVOS models its own heterogeneous population of passenger agents that interact with airlines; this interaction allows the model to simulate the cycle of action-reaction as airlines compete with each other and engage passengers. We validated a baseline configuration of AIRLINE-EVOS against Airline Origin and Destination Survey (DB1B) data and subject matter expert opinion, and we verified the ATS-EVOS framework and agent behavior logic through scenario-based experiments. These experiments demonstrated AIRLINE-EVOS's capabilities in responding to an input price shock in fuel prices, and to equipage challenges in a series of analyses based on potential incentive policies for best equipped best served, optimal-wind routing, and traffic management initiative exemption concepts..

Horio, Brant M.↗
NASA NTRS2013

Aviation Safety: Modeling and Analyzing Complex Interactions between Humans and Automated Systems

The on-going transformation from the current US Air Traffic System (ATS) to the Next Generation Air Traffic System (NextGen) will force the introduction of new automated systems and most likely will cause automation to migrate from ground to air. This will yield new function allocations between humans and automation and therefore change the roles and responsibilities in the ATS. Yet, safety in NextGen is required to be at least as good as in the current system. We therefore need techniques to evaluate the safety of the interactions between humans and automation. We think that current human factor studies and simulation-based techniques will fall short in front of the ATS complexity, and that we need to add more automated techniques to simulations, such as model checking, which offers exhaustive coverage of the non-deterministic behaviors in nominal and off-nominal scenarios. In this work, we present a verification approach based both on simulations and on model checking for evaluating the roles and responsibilities of humans and automation. Models are created using Brahms (a multi-agent framework) and we show that the traditional Brahms simulations can be integrated with automated exploration techniques based on model checking, thus offering a complete exploration of the behavioral space of the scenario. Our formal analysis supports the notion of beliefs and probabilities to reason about human behavior. We demonstrate the technique with the Ueberligen accident since it exemplifies authority problems when receiving conflicting advices from human and automated systems.

Muti-agent System↗
NASA NTRS2014

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↗
NASA NTRS2013

An Investigation of Flight Deck Data Link in the Terminal Area

The Next Generation Air Transportation System (NextGen) and Europe's Single European Sky ATM Research (SESAR) concepts require an increased use of trajectory-based operations, including extensive strategic air traffic control clearances. The clearances are lengthy and complex, which necessitate data link communications to allow for message permanence and integration into the autoflight systems (i.e., autoload capability). This paper examines the use of flight deck data link communications for strategic and tactical clearance usage in the terminal area. A human-in-the-loop simulation was conducted using a high-fidelity flight deck simulator, with ten commercial flight crews as participants. Data were collected from six flight scenarios in the San Francisco terminal airspace. The variables of interest were ATC message modality (voice v. data link), temporal quality of the message (tactical v. strategic) and message length. Dependent variables were message response times, communication clarifications, communication-related errors, and pilot workload. Response time results were longer in data link compared to voice, a finding that has been consistently revealed in a number of other simulations [1]. In addition, strategic clearances and longer messages resulted in a greater number of clarifications and errors, suggesting an increase in uncertainty of message interpretation for the flight crews when compared to tactical clearances. The implications for strategic and compound clearance usage in NextGen and SESAR are discussed

data link communication↗
NASA NTRS2014

A Study of Future Communications Concepts and Technologies for the National Airspace System-Part III

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is investigating current and anticipated wireless communications concepts and technologies that the National Airspace System (NAS) may need in the next 50 years. NASA has awarded three NASA Research Announcements (NAR) studies with the objective to determine the most promising candidate technologies for air-to-air and air-to-ground data exchange and analyze their suitability in a post-NextGen NAS environment. This paper will present progress made in the studies and describe the communications challenges and opportunities that have been identified as part of the study. NASA's NextGen Concepts and Technology Development (CTD) Project integrates solutions for a safe, efficient and high-capacity airspace system through joint research efforts and partnerships with other government agencies. The CTD Project is one of two within NASA's Airspace Systems Program and is managed by the NASA Ames Research Center. Research within the CTD Project is in support the 2011 NASA Strategic Plan Sub-Goal 4.1: Develop innovative solutions and advanced technologies, through a balanced research portfolio, to improve current and future air transportation. The focus of CTD is on developing capabilities in traffic flow management, dynamic airspace configuration, separation assurance, super density operations and airport surface operations. Important to its research is the development of human/automation information requirements and decisionmaking guidelines for human-human and human-machine airportal decision-making. Airborne separation, oceanic intrail climb/descent and interval management applications depend on location and intent information of surrounding aircraft. ADS-B has been proposed to provide the information exchange, but other candidates such as satellite-based receivers, broadband or airborne internet, and cellular communications are possible candidate's.

Navigation↗
NASA NTRS2014

NASA GRC UAS Project - Communications Modeling and Simulation Development Status

The integration of Unmanned Aircraft Systems (UAS) in the National Airspace represents new operational concepts required in civil aviation. These new concepts are evolving as the nation moves toward the Next Generation Air Transportation System (NextGen) under the leadership of the Joint Planning and Development Office (JPDO), and through ongoing work by the Federal Aviation Administration (FAA). The desire and ability to fly UAS in the National Air Space (NAS) in the near term has increased dramatically, and this multi-agency effort to develop and implement a national plan to successfully address the challenges of UAS access to the NAS in a safe and timely manner is well underway. As part of the effort to integrate UAS in the National Airspace, NASA Glenn Research Center is currently involved with providing research into Communications systems and Communication system operations in order to assist with developing requirements for this implementation. In order to provide data and information regarding communication systems performance that will be necessary, NASA GRC is tasked with developing and executing plans for simulations of candidate future UAS command and control communications, in line with architectures and communications technologies being developed and or proposed by NASA and relevant aviation organizations (in particular, RTCA SC-203). The simulations and related analyses will provide insight into the ability of proposed communications technologies and system architectures to enable safe operation of UAS, meeting UAS in the NAS project goals (including performance requirements, scalability, and interoperability), and ultimately leading to a determination of the ability of NextGen communication systems to accommodate UAS. This presentation, compiled by the NASA GRC Modeling and Simulation team, will provide an update to this ongoing effort at NASA GRC as follow-up to the overview of the planned simulation effort presented at ICNS in 2013. The objective of presentation will be to describe the progress made in developing both a NAS-Wide simulation architecture application and the detailed radiocomm system models for this research, and will present interim data and information compiled in the process of developing these simulation capabilities to date.

Modeling and Simulation↗
NASA NTRS2015

Air Traffic Management Technology Demostration Phase 1 (ATD) Interval Management for Near-Term Operations Validation of Acceptability (IM-NOVA) Experiment

The Interval Management for Near-term Operations Validation of Acceptability (IM-NOVA) experiment was conducted at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) in support of the NASA Airspace Systems Program's Air Traffic Management Technology Demonstration-1 (ATD-1). ATD-1 is intended to showcase an integrated set of technologies that provide an efficient arrival solution for managing aircraft using Next Generation Air Transportation System (NextGen) surveillance, navigation, procedures, and automation for both airborne and ground-based systems. The goal of the IMNOVA experiment was to assess if procedures outlined by the ATD-1 Concept of Operations were acceptable to and feasible for use by flight crews in a voice communications environment when used with a minimum set of Flight Deck-based Interval Management (FIM) equipment and a prototype crew interface. To investigate an integrated arrival solution using ground-based air traffic control tools and aircraft Automatic Dependent Surveillance-Broadcast (ADS-B) tools, the LaRC FIM system and the Traffic Management Advisor with Terminal Metering and Controller Managed Spacing tools developed at the NASA Ames Research Center (ARC) were integrated into LaRC's Air Traffic Operations Laboratory (ATOL). Data were collected from 10 crews of current 757/767 pilots asked to fly a high-fidelity, fixed-based simulator during scenarios conducted within an airspace environment modeled on the Dallas-Fort Worth (DFW) Terminal Radar Approach Control area. The aircraft simulator was equipped with the Airborne Spacing for Terminal Area Routes (ASTAR) algorithm and a FIM crew interface consisting of electronic flight bags and ADS-B guidance displays. Researchers used "pseudo-pilot" stations to control 24 simulated aircraft that provided multiple air traffic flows into the DFW International Airport, and recently retired DFW air traffic controllers served as confederate Center, Feeder, Final, and Tower controllers. Analyses of qualitative data revealed that the procedures used by flight crews to receive and execute interval management (IM) clearances in a voice communications environment were logical, easy to follow, did not contain any missing or extraneous steps, and required the use of an acceptable workload level. The majority of the pilot participants found the IM concept, in addition to the proposed FIM crew procedures, to be acceptable and indicated that the ATD-1 procedures could be successfully executed in a nearterm NextGen environment. Analyses of quantitative data revealed that the proposed procedures were feasible for use by flight crews in a voice communications environment. The delivery accuracy at the achieve-by point was within +/-5 sec, and the delivery precision was less than 5 sec. Furthermore, FIM speed commands occurred at a rate of less than one per minute, and pilots found the frequency of the speed commands to be acceptable at all times throughout the experiment scenarios.

Kibler, Jennifer L.↗
NASA NTRS2014

Subsonic Ultra Green Aircraft Research: Phase II- Volume III-Truss Braced Wing Aeroelastic Test Report

This Test Report summarizes the Truss Braced Wing (TBW) Aeroelastic Test (Task 3.1) work accomplished by the Boeing Subsonic Ultra Green Aircraft Research (SUGAR) team, which includes the time period of February 2012 through June 2014. The team consisted of Boeing Research and Technology, Boeing Commercial Airplanes, Virginia Tech, and NextGen Aeronautics. The model was fabricated by NextGen Aeronautics and designed to meet dynamically scaled requirements from the sized full scale TBW FEM. The test of the dynamically scaled SUGAR TBW half model was broken up into open loop testing in December 2013 and closed loop testing from January 2014 to April 2014. Results showed the flutter mechanism to primarily be a coalescence of 2nd bending mode and 1st torsion mode around 10 Hz, as predicted by analysis. Results also showed significant change in flutter speed as angle of attack was varied. This nonlinear behavior can be explained by including preload and large displacement changes to the structural stiffness and mass matrices in the flutter analysis. Control laws derived from both test system ID and FEM19 state space models were successful in suppressing flutter. The control laws were robust and suppressed flutter for a variety of Mach, dynamic pressures, and angle of attacks investigated.

Bradley, Marty K.↗
NASA NTRS2017

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project KDP-C Review

The topics discussed are the UAS-NAS project life-cycle and ARMD thrust flow down, as well as the UAS environments and how we operate in those environments. NASA's Armstrong Flight Research Center at Edwards, CA, is leading a project designed to help integrate unmanned air vehicles into the world around us. The Unmanned Aircraft Systems Integration in the National Airspace System project, or UAS in the NAS, will contribute capabilities designed to reduce technical barriers related to safety and operational challenges associated with enabling routine UAS access to the NAS. The project falls under the Integrated Systems Research Program office managed at NASA Headquarters by the agency's Aeronautics Research Mission Directorate. NASA's four aeronautics research centers - Armstrong, Ames Research Center, Langley Research Center, and Glenn Research Center - are part of the technology development project. With the use and diversity of unmanned aircraft growing rapidly, new uses for these vehicles are constantly being considered. Unmanned aircraft promise new ways of increasing efficiency, reducing costs, enhancing safety and saving lives 460265main_ED10-0132-16_full.jpg Unmanned aircraft systems such as NASA's Global Hawks (above) and Predator B named Ikhana (below), along with numerous other unmanned aircraft systems large and small, are the prime focus of the UAS in the NAS effort to integrate them into the national airspace. Credits: NASA Photos 710580main_ED07-0243-37_full.jpg The UAS in the NAS project envisions performance-based routine access to all segments of the national airspace for all unmanned aircraft system classes, once all safety-related and technical barriers are overcome. The project will provide critical data to such key stakeholders and customers as the Federal Aviation Administration and RTCA Special Committee 203 (formerly the Radio Technical Commission for Aeronautics) by conducting integrated, relevant system-level tests to adequately address safety and operational challenges of national airspace access by unmanned aircraft systems, or UAS. In the process, the project will work with other key stakeholders to define necessary deliverables and products to help enable such access. Within the project, NASA is focusing on five sub-projects. These five focus areas include assurance of safe separation of unmanned aircraft from manned aircraft when flying in the national airspace; safety-critical command and control systems and radio frequencies to enable safe operation of UAS; human factors issues for ground control stations; airworthiness certification standards for UAS avionics and integrated tests and evaluation designed to determine the viability of emerging UAS technology. Five Focus Areas of the UAS Integration in the NAS Project Separation Assurance Provide an assessment of how planned Next Generation Air Transportation System (NextGen) separation assurance systems, with different functional allocations, perform for UAS in mixed operations with manned aircraft Assess the applicability to UAS and the performance of NASA NextGen separation assurance systems in flight tests with realistic latencies and uncertain trajectories Assess functional allocations ranging from today's ground-based, controller-provided aircraft separation to fully autonomous airborne self-separation Communications Develop data and rationale to obtain appropriate frequency spectrum allocations to enable safe and efficient operation of UAS in the NAS Develop and validate candidate secure safety-critical command and control system/subsystem test equipment for UAS that complies with UAS international/national frequency regulations, standards and recommended practices and minimum operational and aviation system performance standards for UAS Perform analysis to support recommendations for integration of safety-critical command and control systems and air traffic control communications to ensure safe and efficient operation of UAS in the NAS Human Systems Integration Develop a research test bed and database to provide data and proof of concept for GCS - ground control station - operations in the NAS Coordinate with standards organizations to develop human-factors guidelines for GCS operation in the NAS Certification Define a UAS classification scheme and approach to determining Federal Aviation Regulation airworthiness requirements applicable to all UAS digital avionics Provide hazard and risk-related data to support development of type design criteria and best development practices Integrated Tests and Evaluation Integrate and test mature concepts from technical elements to demonstrate and test viability Evaluate the performance of technology development in a relevant environment (full-mission, human-in-the-loop simulations and flight tests)

outreach↗
NASA NTRS2017

Preliminary Investigation of Impact of Technological Impairment on Trajectory-Based Operations

The Next Generation Air Transportation System (NextGen) incorporates collaborative air traffic management and Trajectory-Based Operations (TBO) in order to significantly increase the capacity, efficiency, and predictability of operations in the National Airspace System (NAS), without decreasing safety. This is enabled by airspace users and service providers sharing knowledge about operations that allows prediction of the complete 4D flight trajectory with as little uncertainty as possible. Additionally, new software and hardware technology is critical to reaching NextGen goals, especially with regard to TBO. What if the technologies that are critical for TBO were to be impaired or fail completely? Should there be a malfunction of a piece of the technology, it must be ensured that the whole system does not break down completely or suffer severe impairment. Instead, operations need to be maintained proportionally to the problem and safety needs to be ensured (graceful degradation). This paper proposes a systematic framework to investigate the vulnerability of TBO to technology disruption, and determine the impact of technological impairment on TBO. Two representative technologies are chosen for detailed investigation and the impact of their impairment on the degradation of TBO is illustrated using a weather-related scenario. XXXX There are several possible directions of future work. We believe it is desirable to develop methods to quantitatively assess the impact of technological disruption on TBO and to have the simulation tools to validate the impact. The availability of prognostics and health management methods could be leveraged to predict technological failure/disruption, thus predicting how TBO will be a ected, and possibly pro-actively mitigating the impact. It is important to develop large-scale scenarios where the e ect of technological impairment is prominent, and identify methods to quantitatively assess the extent of TBO degradation. An important goal of such an investigation is the development of failure-resistant resilient trajectory-based oper- ations. Resilience14, 15 is the property of a system to \bounce back" and resume at least a signi cant portion of its functionalities after degradation due to technological impairment(s). A systems resilience includes properties such as \bu ering capacity" (quantifying disruptions the system can absorb or adapt to without a fundamental breakdown in performance or in the systems structure), \ exibility" (ability to restructure itself in response to external changes or pressures), "margin" (how closely the system is currently operating rela- tive to one or another kind of performance boundary), \tolerance" (whether the system gracefully degrades as stress/pressure increase, or collapses quickly when pressure exceeds adaptive capacity), etc. Future work needs to focus on quantifying and improving the resilience of TBO, and identifying resilient design solutions for aviation.

TBO↗
NASA NTRS2017

Development of a High-Fidelity Simulation Environment for Shadow-Mode Assessments of Air Traffic Concepts

This paper will describe the purpose, architecture, and implementation of a gate-to-gate, high-fidelity air traffic simulation environment called the Shadow Mode Assessment using Realistic Technologies for the National Airspace System (SMART-NAS) Test Bed.The overarching purpose of the SMART-NAS Test Bed (SNTB) is to conduct high-fidelity, real-time, human-in-the-loop and automation-in-the-loop simulations of current and proposed future air traffic concepts for the Next Generation Air Transportation System of the United States, called NextGen. SNTB is intended to enable simulations that are currently impractical or impossible for three major areas of NextGen research and development: Concepts across multiple operational domains such as the gate-to-gate trajectory-based operations concept; Concepts related to revolutionary operations such as the seamless and widespread integration of large and small Unmanned Aerial System (UAS) vehicles throughout U.S. airspace; Real-time system-wide safety assurance technologies to allow safe, increasingly autonomous aviation operations. SNTB is primarily accessed through a web browser. A set of secure support services are provided to simplify all aspects of real-time, human-in-the-loop and automation-in-the-loop simulations from design (i.e., prior to execution) through analysis (i.e., after execution). These services include simulation architecture and asset configuration; scenario generation; command, control and monitoring; and analysis support.

human-in-the-loop↗
NASA NTRS2018

Using ADOPT Algorithm and Operational Data to Discover Precursors to Aviation Adverse Events

The US National Airspace System (NAS) is making its transition to the NextGen system and assuring safety is one of the top priorities in NextGen. At present, safety is managed reactively (correct after occurrence of an unsafe event). While this strategy works for current operations, it may soon become ineffective for future airspace designs and high density operations. There is a need for proactive management of safety risks by identifying hidden and "unknown" risks and evaluating the impacts on future operations. To this end, NASA Ames has developed data mining algorithms that finds anomalies and precursors (high-risk states) to safety issues in the NAS. In this paper, we describe a recently developed algorithm called ADOPT that analyzes large volumes of data and automatically identifies precursors from real world data. Precursors help in detecting safety risks early so that the operator can mitigate the risk in time. In addition, precursors also help identify causal factors and help predict the safety incident. The ADOPT algorithm scales well to large data sets and to multidimensional time series, reduce analyst time significantly, quantify multiple safety risks giving a holistic view of safety among other benefits. This paper details the algorithm and includes several case studies to demonstrate its application to discover the "known" and "unknown" safety precursors in aviation operation.

aviation safet↗
NASA NTRS2019

Flyover-Noise Reduction of Commercial Aircraft via Reduced Slat Deflections and Modified Flight Procedures

Current regulation and operation of commercial aircraft result in flyover noise that generates public protest from residents well outside the recognized noise footprint of modern airports. This noise issue was recently exacerbated by the implementation of NextGen air-traffic control which uses GPS-navigation for predictable flight paths and improved efficiency. A side-effect of the narrow flight corridors is a perceived increase in noise level and annoyance experienced by the residents directly under the flight paths. As a possible solution to the community noise issue, the feasibility of a lower slat deflections and modified flight procedures were explored. To document the maximum potential noise reduction, field measurements were conducted on the ground at locations before and after slat deployment. For safety considerations, the stall margin of a lower slat deflection was computed for a realistic geometry based on a modern commercial aircraft. The logistics of setting lower slat angles on current aircraft were also investigated through discussions with the FAA (Federal Aviation Administration) and aircraft manufacturers. The results suggest that community flyover noise could be reduced via lower slat deflections during early approach, but that modifying current aircraft would be difficult due to existing control systems and hurdles in certification. Alternatively, modifications to existing flight procedures could reduce the perceived noise of the NextGen flight patterns. For next generation commercial aircraft, reduced slat deflections could be considered if mandated by FAA noise requirements during early approach.

Storms, Bruce L.↗
NASA NTRS2014

A Closer Look at Automation Behavior During a Human-in-the-Loop Simulation

A 2012 Human-In-The-Loop air traffic control simulation investigated a gradual paradigm-shift in the allocation of functions between operators and automation. Air traffic controllers staffed five adjacent high-altitude en route sectors, and during the course of a two-week experiment, worked traffic under four different function allocation concepts aligned with increasingly mature NextGen operational environments. These NextGen time-frames ranged from near current-day operations to nearly fully-automated control, in which the ground systems automation was responsible for detecting conflicts, issuing strategic and tactical resolutions, and alerting controllers to exceptional circumstances. This paper continues the investigations reported in previous publications. Analyses of data surrounding the conflict-resolution task serve as the context in which we investigate the interactions between controllers and the automation.

Human-Automation Interaction↗
NASA NTRS2014

Automated Discovery of Flight Track Anomalies

As new technologies are developed to handle the complexities of the Next Generation Air Transportation System (NextGen), it is increasingly important to address both current and future safety concerns along with the operational, environmental, and efficiency issues within the National Airspace System (NAS). In recent years, the Federal Aviation Administration’s (FAA) safety offices have been researching ways to utilize the many safety databases maintained by the FAA, such as those involving flight recorders, radar tracks, weather, and many other high- volume sensors, in order to monitor this unique and complex system. Although a number of current technologies do monitor the frequency of known safety risks in the NAS, very few methods currently exist that are capable of analyzing large data repositories with the purpose of discovering new and previously unmonitored safety risks. While monitoring the frequency of known events in the NAS enables mitigation of already identified problems, a more proactive approach of finding unidentified issues still needs to be addressed. This is especially important in the proactive identification of new, emergent safety issues that may result from the planned introduction of advanced NextGen air traffic management technologies and procedures. Development of an automated tool that continuously evaluates the NAS to discover both events exhibiting flight characteristics indicative of safety-related concerns as well as operational anomalies will heighten the awareness of such situations in the aviation community and serve to increase the overall safety of the NAS. This paper discusses the extension of previous anomaly detection work to identify operationally significant flights within the highly complex airspace encompassing the New York area of operations, focusing on the major airports of Newark International (EWR), LaGuardia International (LGA), and John F. Kennedy International (JFK). In addition, flight traffic in the vicinity of Denver International (DEN) airport/airspace is also investigated to evaluate the impact on operations due to variances in seasonal weather and airport elevation. From our previous research, subject matter experts determined that some of the identified anomalies were significant, but could not reach conclusive findings without additional supportive data. To advance this research further, causal examination using domain experts is continued along with the integration of air traffic control (ATC) voice data to shed much needed insight into resolving which flight characteristic(s) may be impacting an aircraft's unusual profile. Once a flight characteristic is identified, it could be included in a list of potential safety precursors. This paper also describes a process that has been developed and implemented to automatically identify and produce daily reports on flights of interest from the previous day.

Matthews, Bryan↗
NASA NTRS2015

Terminal Sequencing and Spacing (TSS)

The Federal Aviation Administration's (FAA) Next Generation Air Transportation System (or NextGen) is being designed to support the predicted increases in traffic volume and to increase the capacity, efficiency and safety of the National Airspace System (NAS). The Federal Aviation Administration (FAA) identifies Performance-Based Navigation (PBN) as a key enabling capability of NextGen and is actively publishing PBN procedures at major airports throughout the United States. Standard Terminal Arrival Routes (STARs), procedures, and approaches are designed to facilitate fuel-efficient continuous descent operations. However, their use is limited during periods of high traffic demand due to the complexity of merging multiple streams of aircraft to the same airport. As a result, most arrivals in the Terminal Radar Approach Control (TRACON) area continue to be controlled using radar vectoring and step-down descents, resulting in high workload for controllers and diverting aircraft from efficient PBN trajectories. To address this issue, NASA developed the Terminal Sequencing and Spacing (TSS) system, an advanced arrival management technology that combines time-based scheduling and controller-based precision spacing tools. TSS is a ground-based controller automation tool that facilitates sequencing and merging arrivals on Performance-Based Navigation (PBN) routes, especially during highly congested demand periods. The two main components of TSS are: 1) a scheduler that de-conflicts merging arrivals in the terminal area by computing appropriate arrival times to the runway threshold and upstream terminal merge points, and 2) a set of Controller-Managed Spacing (CMS) decision support tools to efficiently assist schedule conformance. Sixteen high-fidelity human-in-the-loop simulations involving more than five hundred hours of evaluation time, were conducted to mature TSS from proof-of-concept design to a fully functional prototype. Results indicate high controller use and acceptability of the CMS tools as well as improved PBN route conformance (Figure 2). The TSS technology was transferred to the FAA in 2014, and it is targeted for deployment to several busy airports in the U.S. starting in 2018. Potential enhancements to TSS using DataComm will also be presented.

controller-managed spacing↗
NASA NTRS2019

Airborne Spacing for Terminal Arrival Routes (ASTAR) Proof-of-Concept Flight Test

The Airborne Spacing for Terminal Arrival Routes (ASTAR) Flight Test was conducted by the NASA Air Traffic Management Technology Demonstration – 1 (ATD- 1) project to demonstrate the use of NASA’s ASTAR algorithm beyond a simulated environment and assess the operational risks of performing a multi-aircraft flight test of Flight-deck Interval Management (FIM). Utilizing contemporary tools of the Federal Aviation Administration’s Next Generation Air Transportation System (NextGen) such as ADS-B, the ASTAR algorithm calculated speeds that the flight crew flew to achieve a precise spacing interval behind another aircraft at the final approach fix. Airspeed commands issued by the algorithm were flown by the flight crew of the FIM-equipped aircraft to achieve or maintain an assigned spacing goal from a target vehicle. The ASTAR algorithm was integrated with the Boeing supplied B-787 ecoDemonstrator aircraft, and five flight trials were conducted as a joint effort between NASA and Boeing on December 12, 2014. Initial results indicated arrival times within several seconds of accuracy of the planned termination point between two aircraft performing FIM in a real world environment. This flight test opened the way for the much more expansive ATD-1 Avionics Phase II flight test which occurred in early 2017. The flight trials under Phase II preceded further testing by the community in preparation for inclusion of the Interval Management concept as a part of the NextGen environment.

Roper, Roy D.↗