Results for “airspace management” — Page 8

NASA NTRS2009

Human Factors Issues in the Design of Super-Dense Operations Airspace

A knowledge acquisition study was completed focusing on two questions: 1. What is a concept of operation for the design and use of Super-Dense Operations (SDO) airspace within the next 10 years? 2. What are the human factors issues that need to be addressed in order to enable this concept of operation? To address these questions, a series of structured interviews were conducted with four FAA specialists with significant experience as controllers, traffic managers and airspace designers and with one experienced commercial pilot. The operational concept developed based on the expertise of these individuals has similarities to proposals under the FAA's "Big Airspace" project, making heavy use of advanced Area navigation (RNAV) routes, but goes beyond the current state of that concept by making explicit a number of foundational assumptions, and by proposing a system design to deal with convective weather.

Smith, P.J.↗

NASA NTRSDate not supplied

Integrating Upper Class E Traffic Management (ETM) Operations into the National Airspace System: Use Cases and Research Questions

As new categories of vehicles are introduced in the National Airspace System, so too are novel concepts for a cooperative approach to traffic management environments. One of these new environments, Upper Class E Traffic Management (ETM), is expected to include a variety of high altitude, long endurance vehicles with a range of performance capabilities and mission profiles that operate in cooperative areas above 60,000 feet. In addition to developing the rules, architecture, and systems for operations within the ETM environment itself, it is also important to consider how ETM vehicles will integrate with traditional Air Traffic Management and interact with Air Traffic Control (ATC) as they traverse ATC-controlled airspace and transition in and out of cooperative ETM operating areas. As a first step toward future ETM demonstrations at the National Aeronautics and Space Administration (NASA) Ames Research Center’s Airspace Operations Laboratory, use cases with step-by-step procedures were developed to identify both nominal and off-nominal scenarios in which ETM operations will interact with ATC. As NASA prepares to develop a simulation platform to demonstrate ETM cooperative practices and ETM-ATC interactions, the procedures, ATC roles and responsibilities, data exchange requirements, and research questions that were identified as part of use case development will inform scenario and system architecture design. The upcoming simulation work will include initial prototype ETM-ATC coordination tools to support ATC controllers’ interactions with ETM operations. This paper will briefly discuss NASA’s upcoming ETM development work and then provide background on ETM-ATC interactions, describe each ETM-ATC interaction use case, and discuss open questions on concept, procedures, and assumptions.

ATC↗

NASA NTRSDate not supplied

Integrating Upper Class E Traffic Management (ETM) Operations into the National Airspace System: Use Cases and Research Questions

As new categories of vehicles are introduced in the National Airspace System, so too are novel concepts for a cooperative approach to traffic management environments. One of these new environments, Upper Class E Traffic Management (ETM), is expected to include a variety of high altitude, long endurance vehicles with a range of performance capabilities and mission profiles that operate in cooperative areas above 60,000 feet. In addition to developing the rules, architecture, and systems for operations within the ETM environment itself, it is also important to consider how ETM vehicles will integrate with traditional Air Traffic Management and interact with Air Traffic Control (ATC) as they traverse ATC-controlled airspace and transition in and out of cooperative ETM operating areas. As a first step toward future ETM demonstrations at the National Aeronautics and Space Administration (NASA) Ames Research Center’s Airspace Operations Laboratory, use cases with step-by-step procedures were developed to identify both nominal and off-nominal scenarios in which ETM operations will interact with ATC. As NASA prepares to develop a simulation platform to demonstrate ETM cooperative practices and ETM-ATC interactions, the procedures, ATC roles and responsibilities, data exchange requirements, and research questions that were identified as part of use case development will inform scenario and system architecture design. The upcoming simulation work will include initial prototype ETM-ATC coordination tools to support ATC controllers’ interactions with ETM operations. This paper will briefly discuss NASA’s upcoming ETM development work and then provide background on ETM-ATC interactions, describe each ETM-ATC interaction use case, and discuss open questions on concept, procedures, and assumptions.

ATC↗

NASA NTRS2023

Vertiport Dynamic Density

Advanced Air Mobility (AAM) is envisioned to be another spoke in a region’s transportation system, supplementing ground-based travel with air-based travel. Eventually, air taxis will be pervasive, convenient, and affordable. As demand and operations tempo increase, congestion may arise. Several characteristics of AAM reduce the applicability of techniques used in today’s National Airspace System (NAS) to manage congestion. AAM will include both scheduled and non-scheduled, on-demand operations, challenging strategic deconfliction algorithms. Flights will be fairly short, traversing an urban area, not hundreds or thousands of miles, with corresponding low energy reserves, prohibiting excessive delays. Flight operators will need flexibility in operations, scheduling a flight only minutes before departure, or diverting to an alternate vertiport if it becomes advantageous, further adding to trajectory uncertainty that would challenge strategic deconfliction. Finally, operators will desire privacy to protect sensitive information or preserve competitive advantage, limiting early access to intent information. In this paper, we present an approach for managing congestion at vertiports by providing insight into the traffic situation to support operationally-advantageous and safe land or divert decisions. We propose a metric designed with usefulness and usability in AAM operations in mind. The metric uses the sociology concept of dynamic density (DD) that takes into consideration not only number of flights, but also the interaction of those flights with the vertiport’s limited resources, namely the landing pads and the parking spots. DD supports a Pilot in Command (PIC) with decisions about whether to proceed, expedite, delay, or divert; and supports air traffic control (ATC) and vertiport operators in airspace management and vertiport usage. We demonstrate the metric on a notional vertiport scenario. We also show that DD provides better insight into congestion and resulting flight delays than an aircraft count metric used in traditional air traffic management.

Lilly Spirkovska↗

NASA NTRS2019

A Scheduling Algorithm Compatible with a Distributed Management of Arrivals in the National Airspace System

The current system used by the FAA to schedule arrivals is the Traffic Based Flow Manager (TBFM). It is a centralized system that gives an operator (airline) no influence over scheduled times of arrival assigned to its flights. Future systems for managing arrival scheduling are proposed as distributed systems. Such a system is called upon to give operators influence to schedule and negotiate resources for their flights, and to resolve other technical challenges, such as eliminating a single point of failure. A distributed system for managing diverse air traffic will need the capability of computing a schedule for the given arriving flights in a way that complies with the operational constraints. This paper contributes an algorithm that computes such a schedule. Although developed as part of an effort toward a distributed system, the algorithm itself is neither inherently distributed nor inherently centralized and can be used in either type of system.

negotiation↗

NASA NTRS2019

A Scheduling Algorithm Compatible with a Distributed Management of Arrivals in the National Airspace System

The current system used by the FAA to schedule arrivals is the Traffic Based Flow Manager (TBFM). It is a centralized system that gives an operator (airline) no influence over scheduled times of arrival assigned to its flights. Future systems for managing arrival scheduling are proposed as distributed systems. Such a system is called upon to give operators influence to schedule and negotiate resources for their flights, and to resolve other technical challenges, such as eliminating a single point of failure. A distributed system for managing diverse air traffic will need the capability of computing a schedule for the given arriving flights in a way that complies with the operational constraints. This paper contributes an algorithm that computes such a schedule. Although developed as part of an effort toward a distributed system, the algorithm itself is neither inherently distributed nor inherently centralized and can be used in either type of system.

Sadovsky, A.↗

NASA NTRS2002

A Flight Deck Decision Support Tool for Autonomous Airborne Operations

NASA is developing a flight deck decision support tool to support research into autonomous operations in a future distributed air/ground traffic management environment. This interactive real-time decision aid, referred to as the Autonomous Operations Planner (AOP), will enable the flight crew to plan autonomously in the presence of dense traffic and complex flight management constraints. In assisting the flight crew, the AOP accounts for traffic flow management and airspace constraints, schedule requirements, weather hazards, aircraft operational limits, and crew or airline flight-planning goals. This paper describes the AOP and presents an overview of functional and implementation design considerations required for its development. Required AOP functionality is described, its application in autonomous operations research is discussed, and a prototype software architecture for the AOP is presented.

Ballin, Mark G.↗

NASA NTRS2005

NASA and The Semantic Web

We provide an overview of several ongoing NASA endeavors based on concepts, systems, and technology from the Semantic Web arena. Indeed NASA has been one of the early adopters of Semantic Web Technology and we describe ongoing and completed R&D efforts for several applications ranging from collaborative systems to airspace information management to enterprise search to scientific information gathering and discovery systems at NASA.

Ashish, Naveen↗

NASA NTRS2004

Small Aircraft Transportation System Concept and Technologies

This paper summarizes both the vision and the early public-private collaborative research for the Small Aircraft Transportation System (SATS). The paper outlines an operational definition of SATS, describes how SATS conceptually differs from current air transportation capabilities, introduces four SATS operating capabilities, and explains the relation between the SATS operating capabilities and the potential for expanded air mobility. The SATS technology roadmap encompasses on-demand, widely distributed, point-to-point air mobility, through hired-pilot modes in the nearer-term, and through self-operated user modes in the farther-term. The nearer-term concept is based on aircraft and airspace technologies being developed to make the use of smaller, more widely distributed community reliever and general aviation airports and their runways more useful in more weather conditions, in commercial hired-pilot service modes. The farther-term vision is based on technical concepts that could be developed to simplify or automate many of the operational functions in the aircraft and the airspace for meeting future public transportation needs, in personally operated modes. NASA technology strategies form a roadmap between the nearer-term concept and the farther-term vision. This paper outlines a roadmap for scalable, on-demand, distributed air mobility technologies for vehicle and airspace systems. The audiences for the paper include General Aviation manufacturers, small aircraft transportation service providers, the flight training industry, airport and transportation authorities at the Federal, state and local levels, and organizations involved in planning for future National Airspace System advancements.

Small aircraft transportation system↗

NASA NTRS2012

Comparison of Controller and Flight Deck Algorithm Performance During Interval Management with Dynamic Arrival Trees (STARS)

Managing the interval between arrival aircraft is a major part of the en route and TRACON controller s job. In an effort to reduce controller workload and low altitude vectoring, algorithms have been developed to allow pilots to take responsibility for, achieve and maintain proper spacing. Additionally, algorithms have been developed to create dynamic weather-free arrival routes in the presence of convective weather. In a recent study we examined an algorithm to handle dynamic re-routing in the presence of convective weather and two distinct spacing algorithms. The spacing algorithms originated from different core algorithms; both were enhanced with trajectory intent data for the study. These two algorithms were used simultaneously in a human-in-the-loop (HITL) simulation where pilots performed weather-impacted arrival operations into Louisville International Airport while also performing interval management (IM) on some trials. The controllers retained responsibility for separation and for managing the en route airspace and some trials managing IM. The goal was a stress test of dynamic arrival algorithms with ground and airborne spacing concepts. The flight deck spacing algorithms or controller managed spacing not only had to be robust to the dynamic nature of aircraft re-routing around weather but also had to be compatible with two alternative algorithms for achieving the spacing goal. Flight deck interval management spacing in this simulation provided a clear reduction in controller workload relative to when controllers were responsible for spacing the aircraft. At the same time, spacing was much less variable with the flight deck automated spacing. Even though the approaches taken by the two spacing algorithms to achieve the interval management goals were slightly different they seem to be simpatico in achieving the interval management goal of 130 sec by the TRACON boundary.

Battiste, Vernol↗

NASA NTRS2015

National Air Space (NAS) Data Exchange Environment Through 2060

NASA's NextGen Concepts and Technology Development (CTD) Project focuses on capabilities to improve safety, capacity and efficiency of the National Air Space (NAS). In order to achieve those objectives, NASA sought industry-Government partnerships to research and identify solutions for traffic flow management, dynamic airspace configuration, separation assurance, super density operations, airport surface operations and similar forward-looking air-traffic modernization (ATM) concepts. Data exchanges over NAS being the key enabler for most of these ATM concepts, the Sub-Topic area 3 of the CTD project sought to identify technology candidates that can satisfy air-to-air and air/ground communications needs of the NAS in the year 2060 timeframe. Honeywell, under a two-year contract with NASA, is working on this communications technology research initiative. This report summarizes Honeywell's research conducted during the second year of the study task.

National Air Space↗

NASA NTRS2019

Overflow Analysis of Unmanned Aircraft Systems

With the increasing presence of unmanned aircraft systems (UAS), or drones, in the national airspace, the management for access and operation of these vehicles is required. NASA’s management approach is being developed under the unmanned aircraft system traffic management (UTM) program. To determine the aerodynamic characteristics of drones, wind tunnel experiments and computation fluid dynamic (CFD) analysis have been conducted. These experiments and analyses are undertaken to understand the flight capabilities of these vehicles in variable head and cross wind conditions. The results of these investigations will provide metrics for the safe operation of these vehicles in and around civil populations and in urban settings. The focus of this paper is to model a drone installed in a wind tunnel for varying pitch attitudes and rotor rpm settings. Specifically, the IRIS drone is modeled in the NASA-Ames 7x10 ft wind tunnel. The tunnel mounting hardware and the tunnel enclosure are modeled along with the IRIS drone geometry. The rotors of the drone are modeled using two methodologies: a rotor disk model and full rotating rotors with moving grids. The results of the analysis are compared with available experimental data to validate the computational approach.

Stremel, Paul M.↗

NASA NTRS2019

Overflow Simulations of Unmanned Aircraft Systems

National airspace, the management for access and operation of these vehicles is required. This management is being developed under the unmanned aircraft system traffic management system (UTM) program. To determine the aerodynamic characteristics of drones, wind tunnel experiments and computation fluid dynamic (CFD) analysis have been conducted. These experiments and analyses are undertaken to understand the flight capabilities of these vehicles in variable head and cross wind conditions. The results of these investigations will provide metrics for the safe operation of these vehicles in and around civil populations and in urban settings. The focus of this paper is to model a drone installed in a wind tunnel for varying pitch attitudes and rotor rpm settings. Specifically, the IRIS drone is modeled in the NASA-Ames 7x10 ft. W/T. The tunnel mounting hardware and the tunnel enclosure are modeled with the IRIS drone geometry. The rotors of the drone are modeled using two methodologies: a rotor disk model and individual blade representations. The results of the analysis are compared with available experimental data to validate the computational approach.

Stremel, Paul M.↗

NASA NTRSDate not supplied

NASA-FAA Technical Interchange Meeting

High level introduction of Digital Information Platform (DIP) objectives as a sub-project under Airspace Traffic Management - Exploration (ATM-X). Important information is emerging in digital form and additional effort is required to utilize this information. DIP will provide the capability to integrate key flight information from multiple sources. DIP is currently in planning phase will take a community-involved, collaborative approach to define and develop the framework. DIP is seeking community and stakeholder input to operational needs, metrics of interest and demonstration contribution. NASA is engaging with the FAA to coordinate feasible operational demonstrations to validate DIP platform and services.

DIP sub-project overview↗

NASA NTRSDate not supplied

Remote Pilot Handoffs in Large UAS Multi-Vehicle Operations: Best Practices and Supportive Technologies

In response to pilot shortages and increasing air cargo demands, NASA's Pathfinding for Airspace with Autonomous Vehicles (PAAV) sub-project conducted the fourth in a series of tabletop studies investigating scalable solutions for integrating large Uncrewed Aircraft Systems (UAS) into the National Airspace System (NAS). This study solicited subject matter expertise to identify solutions to potential challenges for a further term vision, guiding participants through scenario-based discussions where the remote pilot (RP)-to-vehicle ratio has been scaled from 1:1 to m:N. Of those challenges, remote pilot handoffs were found throughout all phases of flight, both in nominal and non-nominal scenarios. The current paper details participant-suggested procedural and technological solutions for overcoming the handoff challenge, including determining the accepting RP, which aircraft to release, the location and timing of the transition, and options for supporting personnel, tools, and automation that could facilitate safe and efficient handoffs.

unmanned aircraft systems (UAS)↗

NASA NTRSDate not supplied

ACERO, Wildfire Damage and Impact of Aerial Support

This presentation offers an overview of the Advanced Capabilities for Emergency Response Operations (ACERO) project, highlighting key accomplishments in FY24 and outlining the plan for the first Technical Challenge, which is scheduled for completion by FY30.

Wildfire airspace management↗

NASA NTRS2016

Unmanned Aerial Systems Traffic Management (UTM): Safely Enabling UAS Operations in Low-Altitude Airspace

Currently, there is no established infrastructure to enable and safely manage the widespread use of low-altitude airspace and UAS flight operations. Given this, and understanding that the FAA faces a mandate to modernize the present air traffic management system through computer automation and significantly reduce the number of air traffic controllers by FY 2020, the FAA maintains that a comprehensive, yet fully automated UAS traffic management (UTM) system for low-altitude airspace is needed. The concept of UTM is to begin by leveraging concepts from the system of roads, lanes, stop signs, rules and lights that govern vehicles on the ground today. Building on its legacy of work in air traffic management (ATM), NASA is working with industry to develop prototype technologies for a UAS Traffic Management (UTM) system that would evolve airspace integration procedures for enabling safe, efficient low-altitude flight operations that autonomously manage UAS operating in an approved low-altitude airspace environment. UTM is a cloud-based system that will autonomously manage all traffic at low altitudes to include UASs being operated beyond visual line of sight of an operator. UTM would thus enable safe and efficient flight operations by providing fully integrated traffic management services such as airspace design, corridors, dynamic geofencing, severe weather and wind avoidance, congestion management, terrain avoidance, route planning re-routing, separation management, sequencing spacing, and contingency management. UTM removes the need for human operators to continuously monitor aircraft operating in approved areas. NASA envisions concepts for two types of UTM systems. The first would be a small portable system, which could be moved between geographical areas in support of operations such as precision agriculture and public safety. The second would be a Persistent system, which would support low-altitude operations in an approved area by providing continuous automated coverage. Both would require persistent communication, navigation, and surveillance (CNS) coverage to track, ensure, and monitor conformance. UTM is creating an airspace management tool that allows the ATM system to accommodate the number of UAS that will operate in the low altitude airspace. The analogy is just because we have a car, whether its autonomous or someone is driving, does not diminish the need for a road or road signs or rules of the road.

traffic management↗

NASA NTRSDate not supplied

Development of an Airspace Simulation and Modeling Tool for Enhanced Spectrum Management

The emergence of new aerial vehicles into the National Airspace System creates an increased demand for aeronautical communications to support aviation operations. However, the issue of spectrum scarcity remains an ever-present concern, and the growing demand cannot be supported using existing spectrum allocation strategies. As a result, a new spectrum management approach is required, and the National Aeronautics and Space Administration (NASA) is investigating advanced concepts to modernize the management and use of aviation spectrum by leveraging the latest advancements in wireless communications, big data and machine learning. This research proposes an autonomous spectrum allocation concept, which allocates communications resources, such as spectrum and power, based on the predicted communications and air traffic demands throughout the airspace, as opposed to the use of fixed allocations as is done today. This approach will result in improved spectrum utilization efficiency and enhanced airspace capacity. The autonomous spectrum allocation concept decomposes into three research areas: demand prediction, resource allocation, and use case evaluation. As part of the use case evaluation effort, a modeling and simulation capability is currently under development. This simulation capability includes the implementation of various features, including visualization of both live or virtually-generated airspace traffic, simulation scenario development, simulation management with data collection, and flight plan creation with corresponding trajectory generation. This modeling and simulation capability will continue to evolve as new and advanced airspace applications are introduced into existing and emerging operational environments.

Eric J. Knoblock↗