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NASA NTRS2014

Announced Strategy Types in Multiagent RL for Conflict-Avoidance in the National Airspace

The use of unmanned aerial systems (UAS) in the national airspace is of growing interest to the research community. Safety and scalability of control algorithms are key to the successful integration of autonomous system into a human-populated airspace. In order to ensure safety while still maintaining efficient paths of travel, these algorithms must also accommodate heterogeneity of path strategies of its neighbors. We show that, using multiagent RL, we can improve the speed with which conflicts are resolved in cases with up to 80 aircraft within a section of the airspace. In addition, we show that the introduction of abstract agent strategy types to partition the state space is helpful in resolving conflicts, particularly in high congestion.

National Airspace↗

NASA NTRS2020

Tactical Separation and Safety Alerting System for Terminal Airspace

Provision of tactical alerts to aid air traffic controllers in providing separation assurance in terminal airspace is hindered by the complexity of the airspace, its operations, and flight procedures. A prototype automation system is studied that provides controllers with both separation and safety alerts based on or derived from the separation standard for terminal airspace. The system models flight trajectories heuristically, with use of merged intent information from readily available sources: area navigation departure procedures, flight-plan routes, and arrival nominal interior routes used in terminal automation systems. Flight vertical intent is modeled according to standard procedural restrictions except when superseded by controller-issued altitude clearances. Importantly, flight trajectories are modeled for all aircraft, including those conducting visual approaches. New safety-alert thresholds for aircraft conducting visual approaches are studied. Performance of the system is evaluated through fast-time playback of recorded air traffic data from high-fidelity Human-In-The-Loop simulations and real-world operations in two Terminal Radar Approach Control facilities. The prototype system is found to produce a false-alert rate of 8% for separation alerts. The number and validity of safety alerts are studied by comparing with the current Conflict Alert system, showing that the false alerts of Conflict Alert are at 85% and they are avoided in the prototype system.

Air Traffic Management↗

NASA NTRS2021

Simulation and Modeling Concepts for Secure Airspace Operations

This paper examines cyber security vulnerabilities of Urban Air Mobility operations. With the expected advent of new entrants including Unmanned Aerial Systems, Commercial Launch Vehicles and Urban Air Mobility aircraft, the future United States National Airspace System will have to evolve to include their operations along with the current commercial, general aviation and military operations. The National Aeronautics and Space Administration and the Federal Aviation Administration are working together to provide a vision for aviation operations in the future—2045 and beyond. Their National Airspace System Horizons initiative seeks to provide stakeholders a list of operational scenarios and technologies, concepts and strategies needed for supporting that vision. They have identified cybersecurity as one of the seven strategic interest areas for realizing this vision. Consequently, NASA is studying cyber resiliency for secure airspace operations. While there are many pathways to attack a cyber physical system such as Urban Air Mobility, their effect is expressed in modification or corruption of data/information used for controlling vehicles and making operational decisions. The paper describes cybersecurity technologies of Encryption, Blockchain, Virtual Information Fabric Infrastructure, Trusted Platform Module and Anomaly Detection for protecting the data, and the cyber resiliency of the current and future air traffic management system.

Urban Air Mobility↗

NASA NTRS2021

Simulation and Modeling Concepts for Secure Airspace Operations

Urban Air Mobility↗

NASA NTRS2021

UAM Airspace Research Roadmap

The UAM Airspace research roadmap defined herein is expected to be an important tool for the execution of NASA’s research over the next ten years, with the goal of evolving UAM airspace to UML-4. It provides a basis for prioritizing and coordinating research efforts, and for integrating results that build towards NASA’s research goals. The roadmap also has the potential to serve as a focal point for ongoing and continuous deliberation, as has been the case during its development. It naturally attracts questions and feedback that are beneficial to overall understanding, which is key to NASA’s leadership in defining the airspace of the future.

UAM, MBSE, System Engineering, AAM, Airspace, NAS ↗

NASA NTRSDate not supplied

Urban Air Mobility Airspace Dynamic Density

Effective flight planning requires information about a variety of potential threats, such as adverse weather or airspace restrictions, and about alternatives available if unforeseen events occur. Expected traffic along the route of flight is also essential to a safe outcome so that, for example, adequate fuel/energy supply can be loaded prior to flight. A dynamic density (DD) metric is introduced for the emerging urban air mobility (UAM) concept to predict airspace congestion that may lead to loss of separation between aircraft or less efficient operations. Using inspiration from dynamic density metric research for traditional air traffic management and a two-way highway analogy, we develop a dynamic density metric for a portion of airspace (aUAM corridor) that aggregates the impact from five factors: aircraft density, density of populous clusters, mean number of aircraft in populous clusters, mean distance between aircraft, and minimum distance between aircraft. This works describes our methodology, rationale, use cases, and visualization techniques to efficiently present the DD metric to an operator for informed decision making. We also present an approach for validating the metric. However, validation remains part of future work.

UAM↗

NASA NTRSDate not supplied

NASA's Research & Development in Airspace Management for Drones, Air Taxis, and Beyond

Today's National Airspace System is extremely safe. Multiple people and organizations are involved in the handling of flights at all phases. We are, however, at the dawn of a new era in aviation where new entrants are emerging from multiple domains. These new entrants will need to be integrated into the airspace safely and given the flexibility to scale. With that integration and flexibility comes the need and responsibility to develop concepts and systems that will work with the regulatory and operational needs of the Federal Aviation Administration while accounting for the needs of industry. NASA is at the leading edge of research, development, and testing across multiple domains to enable the realization of new entrants such as drones, air cargo and taxis, and high altitude vehicles. Addressing the potential for public good coming from these new capabilities is also a NASA focus area. While there has been considerable effort in the engineering aspects of this research, another thrust that is of importance is that of data integration and visualization. With respect to visualization, NASA Ames Research Center has been leading the advancement in data visualization for these new domains and has spent considerable efforts in the exploration of incorporating Augmented and Mixed Reality as a situation awareness platform. This presentation will outline the new developments in airspace integration and tie in NASA's efforts in visualizing the associated operational data.

airspace management↗

NASA NTRS2022

UAM Airspace Research Roadmap - Rev. 1.2

The UAM Airspace research roadmap is being developed as a new System Engineering methodology leveraging Model Based System Engineering (MBSE) capabilities to help organize, integrate, and communicate NASA's UAM airspace research, with the goal of evolving UAM airspace to UML-4. It provides a basis for prioritizing and coordinating research efforts, and for integrating results that build towards NASA’s research goals. Version 1.2 is a development version of the roadmap, shared publicly to serve as a focal point for discussion and feedback leading to a future baselined version (v2.0). This version supersedes earlier publications, and will be superseded itself by later versions.

UAM↗

NASA NTRS2023

UAM Airspace Research Roadmap - Rev. 2.0

The UAM Airspace research roadmap is being developed as a new System Engineering methodology leveraging Model Based System Engineering (MBSE) capabilities to help organize, integrate, and communicate NASA's UAM airspace research, with the goal of evolving UAM airspace to UML-4. It provides a basis for prioritizing and coordinating research efforts, and for integrating results that build towards NASA’s research goals. Version 2.0 is a baseline version of the roadmap, shared publicly to serve as a focal point for discussion and feedback. This version supersedes earlier publications, and will be superseded itself by later versions.

UAM↗

NASA NTRSDate not supplied

Impact of Traffic-Following on Order of Autonomous Airspace Operations

In this paper, we investigate the dynamic emergence of traffic order in a distributed multi-agent system, aiming to minimize inefficiencies that stem from unnecessary structural impositions. We introduce a methodology for developing a dynamically updating traffic pattern map of the airspace by leveraging information about the consistency and frequency of flow directions used by current as well as preceding traffic. Informed by this map, an agent can discern the degree to which it is advantageous to follow traffic by trading off utilities such as time and order. We show that for the traffic levels studied, for low degrees of traffic-following behavior, there is minimal penalty in terms of aircraft travel times while improving the overall orderliness of the airspace. On the other hand, heightened traffic-following behavior may result in increased aircraft travel times, while marginally reducing the overall entropy of the airspace. Ultimately, the methods and metrics presented in this paper can be used to optimally and dynamically adjust an agent’s traffic-following behavior based on these trade-offs.

Airspace Operations↗

NASA NTRSDate not supplied

Impact of Traffic-Following on Order of Autonomous Airspace Operations

We investigate the dynamic emergence of traffic order in a distributed multi-agent system, aiming to minimize inefficiencies that stem from unnecessary structural impositions. We introduce a methodology for developing a dynamically updating traffic pattern map of the airspace by leveraging information about the consistency and frequency of flow directions used by current as well as preceding traffic. Informed by this map, an agent can discern the degree to which it is advantageous to follow traffic by trading off utilities such as time and order. We show that for the traffic levels studied, for low degrees of traffic-following behavior, there is minimal penalty in terms of aircraft travel times while improving the overall orderliness of the airspace. On the other hand, heightened traffic-following behavior may result in increased aircraft travel times, while marginally reducing the overall entropy of the airspace. Ultimately, the methods and metrics presented in this paper can be used to optimally and dynamically adjust an agent’s traffic-following behavior based on these trade-offs.

Airspace Operations↗

NASA NTRS1996

A System Concept for Facilitating User Preferences in En Route Airspace

The Federal Aviation Administration is trying to make its air traffic management system more responsive to the needs of the aviation community by exploring the concept of 'free flight' for aircraft flying under instrument flight rules. A logical first step toward free flight could be made without significantly altering current air traffic control (ATC) procedures or requiring new airborne equipment by designing a ground-based system to be highly responsive to 'user preference' in en route airspace while providing for an orderly transition to the terminal area. To facilitate user preference in all en route environments, a system based on an extension of the Center/TRACON Automation System (CTAS) is proposed in this document. The new system would consist of two integrated components. An airspace tool (AT) focuses on unconstrained en route aircraft (e.g., not transitioning to the terminal airspace), taking advantage of the relatively unconstrained nature of their flights and using long-range trajectory prediction to provide cost-effective conflict resolution advisories to sector controllers. A sector tool (ST) generates efficient advisories for all aircraft, with a focus on supporting controllers in analyzing and resolving complex, highly constrained traffic situations. When combined, the integrated AT/ST system supports user preference in any air route traffic control center sector. The system should also be useful in evaluating advanced free-flight concepts by serving as a test bed for future research. This document provides an overview of the design concept, explains its anticipated benefits, and recommends a development strategy that leads to a deployable system.

Vivona, R. A.↗

NASA NTRS2004

The Processing of Airspace Concept Evaluations Using FASTE-CNS as a Pre- or Post-Simulation CNS Analysis Tool

As NASA speculates on and explores the future of aviation, the technological and physical aspects of our environment increasing become hurdles that must be overcome for success. Research into methods for overcoming some of these selected hurdles have been purposed by several NASA research partners as concepts. The task of establishing a common evaluation environment was placed on NASA's Virtual Airspace Simulation Technologies (VAST) project (sub-project of VAMS), and they responded with the development of the Airspace Concept Evaluation System (ACES). As one examines the ACES environment from a communication, navigation or surveillance (CNS) perspective, the simulation parameters are built with assumed perfection in the transactions associated with CNS. To truly evaluate these concepts in a realistic sense, the contributions/effects of CNS must be part of the ACES. NASA Glenn Research Center (GRC) has supported the Virtual Airspace Modeling and Simulation (VAMS) project through the continued development of CNS models and analysis capabilities which supports the ACES environment. NASA GRC initiated the development a communications traffic loading analysis tool, called the Future Aeronautical Sub-network Traffic Emulator for Communications, Navigation and Surveillance (FASTE-CNS), as part of this support. This tool allows for forecasting of communications load with the understanding that, there is no single, common source for loading models used to evaluate the existing and planned communications channels; and that, consensus and accuracy in the traffic load models is a very important input to the decisions being made on the acceptability of communication techniques used to fulfill the aeronautical requirements. Leveraging off the existing capabilities of the FASTE-CNS tool, GRC has called for FASTE-CNS to have the functionality to pre- and post-process the simulation runs of ACES to report on instances when traffic density, frequency congestion or aircraft spacing/distance violations have occurred. The integration of these functions require that the CNS models used to characterize these avionic system be of higher fidelity and better consistency then is present in FASTE-CNS system. This presentation will explore the capabilities of FASTE-CNS with renewed emphasis on the enhancements being added to perform these processing functions; the fidelity and reliability of CNS models necessary to make the enhancements work; and the benchmarking of FASTE-CNS results to improve confidence for the results of the new processing capabilities.

Mainger, Steve↗

NASA NTRS2004

National Airspace System Delay Estimation Using Weather Weighted Traffic Counts

Assessment of National Airspace System performance, which is usually measured in terms of delays resulting from the application of traffic flow management initiatives in response to weather conditions, volume, equipment outages and runway conditions, is needed both for guiding flow control decisions during the day of operations and for post operations analysis. Comparison of the actual delay, resulting from the traffic flow management initiatives, with the expected delay, based on traffic demand and other conditions, provides the assessment of the National Airspace System performance. This paper provides a method for estimating delay using the expected traffic demand and weather. In order to identify the cause of delays, 517 days of National Airspace System delay data reported by the Federal Aviation Administration s Operations Network were analyzed. This analysis shows that weather is the most important causal factor for delays followed by equipment and runway delays. Guided by these results, the concept of weather weighted traffic counts as a measure of system delay is described. Examples are given to show the variation of these counts as a function of time of the day. The various datasets, consisting of aircraft position data, enroute severe weather data, surface wind speed and visibility data, reported delay data and number of aircraft handled by the Centers data, and their sources are described. The procedure for selecting reference days on which traffic was minimally impacted by weather is described. Different traffic demand on each reference day of the week, determined by analysis of 42 days of traffic and delay data, was used as the expected traffic demand for each day of the week. Next, the method for computing the weather weighted traffic counts using the expected traffic demand, derived from reference days, and the expanded regions around severe weather cells is discussed. It is shown via a numerical example that this approach improves the dynamic range of the weather weighted traffic counts considerably. Time histories of these new weather weighted traffic counts are used for synthesizing two statistical features, six histogram features and six time domain features. In addition to these enroute weather features, two surface weather features of number of major airports in the United States with high mean winds and low mean visibility are also described. A least squares procedure for establishing a functional relation between the features, using combinations of these features, and system delays is explored using 36 days of data. Best correlations between the estimated delays using the functional relation and the actual delays provided by the Operations Network are obtained with two different combinations of features: 1) six time domain features of weather weighted traffic counts plus two surface weather features, and 2) six histogram features and mean of weather weighted traffic counts along with the two surface weather features. Correlation coefficient values of 0.73 and 0.83 were found in these two instances.

Chatterji, Gano B.↗

NASA NTRS2005

Validation Of The Airspace Concept Evaluation System Using Real World Data

This paper discusses the process of performing a validation of the Airspace Concept Evaluation System (ACES) using real world historical flight operational data. ACES inputs are generated from select real world data and processed to create a realistic reproduction of a single day of operations within the National Airspace System (NAS). ACES outputs are then compared to real world operational metrics and delay statistics for the reproduced day. Preliminary results indicate that ACES produces delays and airport operational metrics similar to the real world with minor variations of delay by phase of flight. ACES is a nation-wide fast-time simulation tool developed at NASA Ames Research Center. ACES models and simulates the NAS using interacting agents representing center control, terminal flow management, airports, individual flights, and other NAS elements. These agents pass messages between one another similar to real world communications. This distributed agent based system is designed to emulate the highly unpredictable nature of the NAS, making it a suitable tool to evaluate current and envisioned airspace concepts. To ensure that ACES produces the most realistic results, the system must be validated. There is no way to validate future concepts scenarios using real world historical data, but current day scenario validations increase confidence in the validity of future scenario results. Each operational day has unique weather and traffic demand schedules. The more a simulation utilizes the unique characteristic of a specific day, the more realistic the results should be. ACES is able to simulate the full scale demand traffic necessary to perform a validation using real world data. Through direct comparison with the real world, models may continuee to be improved and unusual trends and biases may be filtered out of the system or used to normalize the results of future concept simulations.

Zelinski, Shannon↗

NASA NTRS2006

Characterization of Days Based On Analysis of National Airspace System Performance Metrics

Days of operations in the National Airspace System can be described in term of traffic demand, runway conditions, equipment outages, and surface and enroute weather conditions. These causes manifest themselves in terms of departure delays, arrival delays, enroute delays and traffic flow management delays, Traffic flow management initiatives such as, ground stops, ground delay programs, miles-in-trail restrictions, rerouting and airborne holding are imposed to balance the air traffic demand with respect to the available capacity, In order to maintain operational efficiency of the National Airspace System, the Federal Aviation Administration (FAA) maintains delay sad other statistics in the Air Traffic Operations Network (OPSNET) and the Aviation System Performance Metrics (ASPM) databases. OPSNET data includes reportable delays of fifteen minutes ox more experienced by Instrument Flight Rule (IFR) flights. Numbers of aircraft affected by departure delays, enroute delays, arrival delays and traffic flow delays are recorded in the OPSNET data. ASPM data consist of number of actual departures, number of canceled departures, percentage of on time departures, percentage of on time gate arrivals, taxi-out delays. taxi-in delays, gate delays, arrival delays and block delays. Surface conditions at the major U.S. airports are classified in terms of Instrument Meteorological Condition (IMC) and Visual Meteorological Condition (VMC) as a function of the time of the day in the ASPM data. The main objective of this paper is to use OPSNET and ASPM data to classify the days in the datasets into few distinct groups, where each group is separated from the other groups in terms of a distance metric. The motivations for classifying the days are two-fold, 1) to enable selection of days of traffic with particular operational characteristics for concept evaluation using system-wide simulation systems such as the National Aeronautics and Space Administration's Airspace Concepts Evaluation Tool (ACES) and 2) to enable evaluation of a given day with respect to the characteristics of the classified groups. The first part of the paper is devoted to the analysis of major trends seen in the OPSNET and ASPM data. The second part of the paper is devoted to describing features or measures derived from the OPSNET and ASPM data that are suitable for characterizing days, and the classification algorithm used for grouping the days. Finally, the method for evaluating the characteristics of a given day with respect to the properties of the groups is described.

Chatterji, Gano B.↗

NASA NTRS2008

Development and Application of an Integrated Approach toward NASA Airspace Systems Research

The National Aeronautics and Space Administration's (NASA) Airspace Systems Program is contributing air traffic management research in support of the 2025 Next Generation Air Transportation System (NextGen). Contributions support research and development needs provided by the interagency Joint Planning and Development Office (JPDO). These needs generally call for integrated technical solutions that improve system-level performance and work effectively across multiple domains and planning time horizons. In response, the Airspace Systems Program is pursuing an integrated research approach and has adapted systems engineering best practices for application in a research environment. Systems engineering methods aim to enable researchers to methodically compare different technical approaches, consider system-level performance, and develop compatible solutions. Systems engineering activities are performed iteratively as the research matures. Products of this approach include a demand and needs analysis, system-level descriptions focusing on NASA research contributions, system assessment and design studies, and common systemlevel metrics, scenarios, and assumptions. Results from the first systems engineering iteration include a preliminary demand and needs analysis; a functional modeling tool; and initial system-level metrics, scenario characteristics, and assumptions. Demand and needs analysis results suggest that several advanced concepts can mitigate demand/capacity imbalances for NextGen, but fall short of enabling three-times current-day capacity at the nation s busiest airports and airspace. Current activities are focusing on standardizing metrics, scenarios, and assumptions, conducting system-level performance assessments of integrated research solutions, and exploring key system design interfaces.

Barhydt, Richard↗

NASA NTRS2009

Using Unmanned Aircraft Systems (UAS) for Remote Sensing: Airspace Access Challenges

Several areas of scientific interest have been identified that would significantly benefit from using Unmanned Aircraft Systems (UAS) for gathering remote sensing data. UAS are uniquely suited for applications that require long dwell times and/or in locations that are generally too dangerous for manned aircraft. Sea ice characterization, mapping of fault lines, hurricane monitoring, and satellite validation are some examples of applications that are benefited by the use of UAS. UAS are not without their challenges, however. Instruments must be automated and miniaturized, and be able to operate in extreme conditions (i.e. high altitude environments). However, because UAS currently lack a see-and-avoid capability, the greatest challenge is getting access to the airspace required to accomplish science missions. The ability for UAS to access airspace varies from country to country. This paper will give a brief overview of different UAS remote sensing applications, and will address general world airspace issues and challenges with a specific look at the United States.

Mulac, Brenda L.↗