SEARCH · Engineering Papers

Results for “traffic management”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3

All sources NASA NTRS DOE OSTI

NASA NTRS2022

Air Traffic Management TestBed: Messaging Performance

The Air Traffic Management (ATM) TestBed is an air traffic management modeling and simulation platform and framework developed by the National Aeronautics and Space Administration (NASA) to help design, configure, integrate, run, and monitor air traffic simulations. The communication middleware, implemented in the TestBed framework layer, is a core feature for data message exchange. The feature provides an abstraction layer called Messaging Support to allow switching one middleware to another without a need to rebuild the simulation components. Messaging performance such as latencies, run durations, and throughputs are important factors. Low latencies can produce accurate results in high-fidelity and visualization models. Short run durations are preferred because better run efficiency can be achieved. High throughputs allow more runs to be executed concurrently. This technical memorandum studies and compares the messaging performance by running a full-day, fast-time simulation using three communication middleware as well as tweaking the default communication middleware settings used by the TestBed. Results indicate that the messaging performance could be improved by disabling either compression or persistence settings, while the run duration and throughput could be further improved by disabling both settings with a tradeoff of the message latencies increased by a factor of ten.

Chok Fung Lai↗

NASA NTRSDate not supplied

Exploring the Effectiveness of Maneuvering Guidelines for Space Traffic Management

The number of objects in space has been increasing rapidly, and the risk of collision has grown as well. Many spacecraft operators are now receiving multiple collision warnings a day. Despite this, systems to manage space traffic have been limited: there are no broadly agreed upon guidelines or rules governing the response to predicted potential collisions. Instead, spacecraft operators generally determine whether, when, and how to respond to these warnings on a manual and ad hoc basis. Coordination between operators, if it occurs, often requires repeated communication and negotiation. Some space actors have suggested that the space community should develop right of way rules, similar to those in the ground, sea, and air domains, to guide collision response decisions. However, it is unclear whether such rules would be effective, and it’s unknown whether such rules would have an equitable impact across various spacecraft operators. To address these issues, we developed the Virtual Environment for Space Traffic Analysis (VESTA), a software tool that was used to simulate the space environment with a recent catalog of objects obtained from the U.S. Space-Track.org system. We implemented multiple potential right of way rules within this model. The analysis confirmed that the choice of right of way rule makes a meaningful difference in terms of both efficiency and distributional effects in terms of collision avoidance maneuvers. For example, our analysis shows that rules in which the less massive satellite is required to maneuver results in a more equitable distribution of maneuver responsibility among space actors and also requires less fuel mass, compared to a rule in which the more massive satellite maneuvers.

space traffic management↗

NASA NTRS1998

Aircraft/Air Traffic Management Functional Analysis Model: Technical Description

The Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 (FAM 2.0), is a discrete event simulation model designed to support analysis of alternative concepts in air traffic management and control. FAM 2.0 was developed by the Logistics Management Institute (LMI) under a National Aeronautics and Space Administration (NASA) contract. This document provides a technical description of FAM 2.0 and its computer files to enable the modeler and programmer to make enhancements or modifications to the model. Those interested in a guide for using the model in analysis should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Users Manual.

Etheridge, Melvin↗

NASA NTRS1997

The Challenges of Field Testing the Traffic Management Advisor (TMA) in an Operational Air Traffic Control Facility

The Traffic Management Advisor (TMA), the sequence and schedule tool of the Center/TRACON Automation System (CTAS), was evaluated at the Fort Worth Center (ZFW) in the summer of 1996. This paper describes the challenges encountered during the various phases of the TMA field evaluation, which included system (hardware and software) installation, personnel training, and data collection. Operational procedures were developed and applied to the evaluation process that would ensure air safety. The five weeks of field evaluation imposed minimal impact on the hosting facility and provided valuable engineering and human factors data. The collection of data was very much an opportunistic affair, due to dynamic traffic conditions. One measure of the success of the TMA evaluation is that, rather than remove TMA after the evaluation until it could be fully implemented, the prototype TMA is in continual use at ZFW as the fully operational version is readied for implementation.

Hoang, Ty↗

NASA NTRS2016

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

Unmanned Aircraft System (UAS) Traffic Management (UTM) Enabling Civilian Low-Altitude Airspace and Unmanned Aircraft System Operations What is the problem? Many beneficial civilian applications of UAS have been proposed, from goods delivery and infrastructure surveillance, to search and rescue, and agricultural monitoring. Currently, there is no established infrastructure to enable and safely manage the widespread use of low-altitude airspace and UAS operations, regardless of the type of UAS. A UAS traffic management (UTM) system for low-altitude airspace may be needed, perhaps leveraging concepts from the system of roads, lanes, stop signs, rules and lights that govern vehicles on the ground today, whether the vehicles are driven by humans or are automated. What system technologies is NASA exploring? Building on its legacy of work in air traffic management for crewed aircraft, NASA is researching prototype technologies for a UAS Traffic Management (UTM) system that could develop airspace integration requirements for enabling safe, efficient low-altitude operations. While incorporating lessons learned from the today's well-established air traffic management system, which was a response that grew out of a mid-air collision over the Grand Canyon in the early days of commercial aviation, the UTM system would enable safe and efficient low-altitude airspace operations by providing services such as airspace design, corridors, dynamic geofencing, severe weather and wind avoidance, congestion management, terrain avoidance, route planning and re-routing, separation management, sequencing and spacing, and contingency management. One of the attributes of the UTM system is that it would not require human operators to monitor every vehicle continuously. The system could provide to human managers the data to make strategic decisions related to initiation, continuation, and termination of airspace operations. This approach would ensure that only authenticated UAS could operate in the airspace. In its most mature form, the UTM system could be developed using autonomicity characteristics that include self-configuration, self-optimization and self-protection. The self-configuration aspect could determine whether the operations should continue given the current andor predicted windweather conditions. NASA envisions concepts for two types of possible UTM systems. The first type would be a Portable UTM system, which would move from between geographical areas and support operations such as precision agriculture and disaster relief. The second type of system would be a Persistent UTM system, which would support low-altitude operations and provide continuous coverage for a geographical area. Either system would require persistent communication, navigation, and surveillance (CNS) coverage to track, ensure, and monitor conformance. What is NASA doing to test the technologies? NASA's near-term goal is the development and demonstration of a possible future UTM system that could safely enable low-altitude airspace and UAS operations. Working alongside many committed government, industry and academic partners, NASA is leading the research, development and testing that is taking place in a series of activities called Technology Capability Levels (TCL), each increasing in complexity. UTM TCL1 concluded field testing in August 2015 and is undergoing additional testing at an FAA site.

UTM Low-altitude↗

NASA NTRS2007

Comprehensive Software Eases Air Traffic Management

To help air traffic control centers improve the safety and the efficiency of the National Airspace System, Ames Research Center developed the Future Air Traffic Management Concepts Evaluation Tool (FACET) software, which won NASA's 2006 "Software of the Year" competition. In 2005, Ames licensed FACET to Flight Explorer Inc., for integration into its Flight Explorer (version 6.0) software. The primary FACET features incorporated in the Flight Explorer software system alert airspace users to forecasted demand and capacity imbalances. Advance access to this information helps dispatchers anticipate congested sectors (airspace) and delays at airports, and decide if they need to reroute flights. FACET is now a fully integrated feature in the Flight Explorer Professional Edition (version 7.0). Flight Explorer Professional offers end-users other benefits, including ease of operation; automatic alerts to inform users of important events such as weather conditions and potential airport delays; and international, real-time flight coverage over Canada, the United Kingdom, New Zealand, and sections of the Atlantic and Pacific Oceans. Flight Explorer Inc. recently broadened coverage by partnering with Honeywell International Inc.'s Global Data Center, Blue Sky Network, Sky Connect LLC, SITA, ARINC Incorporated, Latitude Technologies Corporation, and Wingspeed Corporation, to track their aircraft anywhere in the world.

Source record↗

NASA NTRSDate not supplied

Strategic and Tactical Functions in an Autonomous Air Traffic Management System

This paper evaluates, by means of fast-time simulation, performance of a candidate system for autonomous air traffic management. Advancing towards autonomy in air traffic management may be necessary in order for new air vehicle types such as electric Vertical Take Off and Landing (eVTOL) to operate safely and efficiently in airspace shared with conventional traffic. To account for uncertain prediction, autonomous air traffic management was divided into two integrated and coordinated subsystems: strategic scheduling, performed at predeparture, and tactical conflict detection and resolution, performed throughout the flight. The conflict detection and resolution subsystem contained a second tactical scheduling function that applied to flights operating in the airspace near the destination airport. This paper compares and contrasts the two subsystems and uses fast-time simulation to demonstrate the comparisons. A scenario of 54 flights inbound to Newark Liberty International Airport was simulated multiple times with different parameters. The scenario was created using flight plans recorded from the National Airspace System on a low weather, average traffic day in April 2018. Whereas the routes were not changed, the departure times of the flights were modified to increase arrival rates at the Newark runway and arrival meter fixes. Results of the simulations showed that the autonomous air traffic management system was able to safely manage the traffic, even with prediction uncertainty. In addition, they showed the importance of including flight holding maneuvers, in addition to path stretching, in conflict detection and resolution and of coordinating strategic and tactical scheduling. Finally, a tradeoff between absorbing the delay calculated by strategic scheduling on the ground versus in the air showed that taking most of the delay on the ground is cost effective for a simple idealized cost function. However, taking a little of the delay in the air prevented throughput on the runway from dropping for short periods due to trajectory prediction uncertainty.

air traffic control↗

NASA NTRS2021

Strategic and Tactical Functions in an Autonomous Air Traffic Management System

air traffic control↗

NASA NTRS1998

Airspace Complexity and its Application in Air Traffic Management

The United States Air Traffic Management (ATM) system provides services to enable safe, orderly and efficient aircraft operations within the airspace over the continental United States and over large portions of the Pacific and Atlantic Oceans, and the Gulf of Mexico. It consists of two components, Air Traffic Control (ATC) and Traffic Flow Management (TFM). The ATC function ensures that the aircraft within the airspace are separated at all times while the TFM function organizes the aircraft into a flow pattern to ensure their safe and efficient movement. In order to accomplish the ATC and TFM functions, the airspace over United States is organized into 22 Air Route Traffic Control Centers (ARTCCs). The Center airspace is stratified into low-altitude, high-altitude and super-high altitude groups of Sectors. Each vertical layer is further partitioned into several horizontal Sectors. A typical ARTCC airspace is partitioned into 20 to 80 Sectors. These Sectors are the basic control units within the ATM system.

Sridhar, Banavar↗

NASA NTRSDate not supplied

Predicting Air Traffic Management Initiatives Using Supervised Learning

Terminal Traffic Management Initiatives (TMIs) such as Ground Stops (GS) and Ground Delay Programs (GDP) are implemented to manage excess demand or lowered capacity at an airport. Air Traffic Flow Management (TFM) specialists identify situations such as aviation constraints, current and forecasted weather conditions, airport demand and capacity, and initiate TMIs for safe and orderly movement of air traffic. In this paper, we outline supervised learning techniques that can be used to predict and recommend TMIs at an airport based on current weather and airport conditions. Our research involves building classic Machine Learning (ML) models such as Logistic Regression, K-Nearest Neighbor, Random Forest and XGBoost, as well as Long short-term memory (LSTM) networks. We trained the models on 3-year historical data (weather, airport demand, capacity and TMIs) from Newark (EWR) airport which was selected based on its higher TMI implementation rates and varied weather conditions. Although Random Forest and XGBoost algorithms are able to predict if a TMI is needed or not, they have difficulty in predicting specific program type. For this purpose, we found that LSTM time-series forecasting models performed better as they also learn from past TMI program type sequences. This study also lays down the foundation for advanced modeling techniques and architectures to predict TMIs in advance for future periods. The ability to predict TMIs in advance will be highly beneficial to the traffic controllers and managers as this will help them to prepare for and manage TMIs more efficiently.

Manoj Agrawal↗

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 NTRS2012

A Perspective on NASA Ames Air Traffic Management Research

This paper describes past and present air-traffic-management research at NASA Ames Research Center. The descriptions emerge from the perspective of a technical manager who supervised the majority of this research for the last four years. Past research contributions built a foundation for calculating accurate flight trajectories to enable efficient airspace management in time. That foundation led to two predominant research activities that continue to this day - one in automatically separating aircraft and the other in optimizing traffic flows. Today s national airspace uses many of the applications resulting from research at Ames. These applications include the nationwide deployment of the Traffic Management Advisor, new procedures enabling continuous descent arrivals, cooperation with industry to permit more direct flights to downstream way-points, a surface management system in use by two cargo carriers, and software to evaluate how well flights conform to national traffic management initiatives. The paper concludes with suggestions for prioritized research in the upcoming years. These priorities include: enabling more first-look operational evaluations, improving conflict detection and resolution for climbing or descending aircraft, and focusing additional attention on the underpinning safety critical items such as a reliable datalink.

Schroeder, Jeffery A.↗

NASA NTRS2005

The Effects of the Uncertainty of Departures on Multi-Center Traffic Management Advisor (TMA) Scheduling

The Multi-center Traffic Management Advisor (McTMA) provides a platform for regional or national traffic flow management, by allowing long-range cooperative time-based metering to constrained resources, such as airports or air traffic control center boundaries. Part of the demand for resources is made up of proposed departures, whose actual departure time is difficult to predict. For this reason, McTMA does not schedule the departures in advance, but rather relies on traffic managers to input their requested departure time. Because this happens only a short while before the aircraft's actual departure, McTMA is unable to accurately predict the amount of delay airborne aircraft will need to take in order to accommodate the departures. The proportion of demand which is made up by such proposed departures increases as the horizon over which metering occurs gets larger. This study provides an initial analysis of the severity of this problem in a 400-500 nautical mile metering horizon and discusses potential solutions to accommodate these departures. The challenge is to smoothly incorporate departures with the airborne stream while not excessively delaying the departures.' In particular, three solutions are reviewed: (1) scheduling the departures at their proposed departure time; (2) not scheduling the departures in advance; and (3) scheduling the departures at some time in the future based on an estimated error in their proposed time. The first solution is to have McTMA to automatically schedule the departures at their proposed departure times. Since the proposed departure times are indicated in their flight times in advance, this method is the simplest, but studies have shown that these proposed times are often incorrect2 The second option is the current practice, which avoids these inaccuracies by only scheduling aircraft when a confirmed prediction of departure time is obtained from the tower of the departure airport. Lastly, McTMA can schedule the departures at a predicted departure time based on statistical data of past departure time performance. It has been found that departures usually have a wheels-up time after their indicated proposed departure time, as shown in Figure 1. Hence, the departures were scheduled at a time in the future based on the mean error in proposed departure times for their airport.

Thipphavong, Jane↗

NASA NTRS2019

Prototyping Operational Autonomy for Space Traffic Management

Current state of the art in Space Traffic Management (STM) relies on a handful of providers for surveillance and collision prediction, and manual coordination between operators. Neither is scalable to support the expected 10x increase in spacecraft population in less than 10 years, nor does it support automated manuever planning. We present a software prototype of an STM architecture based on open Application Programming Interfaces (APIs), drawing on previous work by NASA to develop an architecture for low-altitude Unmanned Aerial System Traffic Management. The STM architecture is designed to provide structure to the interactions between spacecraft operators, various regulatory bodies, and service suppliers, while maintaining flexibility of these interactions and the ability for new market participants to enter easily. Autonomy is an indispensable part of the proposed architecture in enabling efficient data sharing, coordination between STM participants and safe flight operations. Examples of autonomy within STM include syncing multiple non-authoritative catalogs of resident space objects, or determining which spacecraft maneuvers when preventing impending conjunctions between multiple spacecraft. The STM prototype is based on modern micro-service architecture adhering to OpenAPI standards and deployed in industry standard Docker containers, facilitating easy communication between different participants or services. The system architecture is designed to facilitate adding and replacing services with minimal disruption. We have implemented some example participant services (e.g. a space situational awareness provider/SSA, a conjunction assessment supplier/CAS, an automated maneuver advisor/AMA) within the prototype. Different services, with creative algorithms folded into then, can fulfil similar functional roles within the STM architecture by flexibly connecting to it using pre-defined APIs and data models, thereby lowering the barrier to entry of new players in the STM marketplace. We demonstrate the STM prototype on a multiple conjunction scenario with multiple maneuverable spacecraft, where an example CAS and AMA can recommend optimal maneuvers to the spacecraft operators, based on a predefined reward function. Such tools can intelligently search the space of potential collision avoidance maneuvers with varying parameters like lead time and propellant usage, optimize a customized reward function, and be implemented as a scheduling service within the STM architecture. The case study shows an example of autonomous maneuver planning is possible using the API-based framework. As satellite populations and predicted conjunctions increase, an STM architecture can facilitate seamless information exchange related to collision prediction and mitigation among various service applications on different platforms and servers. The availability of such an STM network also opens up new research topics on satellite maneuver planning, scheduling and negotiation across disjoint entities.

space traffic management↗

NASA NTRS1998

Aircraft/Air Traffic Management Functional Analysis Model: User's Guide - Version 2.0

The Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 (FAM 2.0), is a discrete event simulation model designed to support analysis of alternative concepts in air traffic management and control. FAM 2.0 was developed by the Logistics Management Institute (LMI) a National Aeronautics and Space Administration (NASA) contract. This document provides a guide for using the model in analysis. Those interested in making enhancements or modification to the model should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Technical Description.

Etheridge, Melvin↗

NASA NTRS1986

A time-based concept for terminal-area traffic management

An automated air-traffic-management concept that has the potential for significantly increasing the efficiency of traffic flows in high-density terminal areas is discussed. The concept's implementation depends on techniques for controlling the landing time of all aircraft entering the terminal area, both those that are equipped with on-board four-dimensional (4D) guidance systems as well as those aircraft types that are conventionally equipped. The two major ground-based elements of the system are a scheduler which assigns conflict-free landing times and a profile descent advisor. Landing time provided by the scheduler is uplinked to equipped aircraft and translated into the appropriate 4D trajectory by the-board flight-management system. The controller issues descent advisories to unequipped aircraft to help them achieve the assigned landing times. Air traffic control simulations have established that the concept provides an efficient method for controlling various mixes of 4D-equipped and unequipped, as well as low- and high-performance, aircraft. Piloted simulations of profiles flown with the aid of advisories have verified the ability to meet specified descent times with prescribed accuracy.

Erzberger, Heinz↗

NASA NTRS1986

A time-based concept for terminal-area traffic management

An automated air-traffic-management concept that has the potential for significantly increasing the efficiency of traffic flows in high-density terminal areas is discussed. The concept's implementation depends on the techniques for controlling the landing time of all aircraft entering the terminal area, both those that are equipped with on-board four dimensional guidance systems as well as those aircraft types that are conventionally equipped. The two major ground-based elements of the system are a scheduler which assigns conflict-free landing times and a profile descent advisor. Landing times provided by the scheduler are uplinked to equipped aircraft and translated into the appropriate four dimensional trajectory by the on-board flight-management system. The controller issues descent advisories to unequipped aircraft to help them achieve the assigned landing times. Air traffic control simulations have established that the concept provides an efficient method for controlling various mixes of four dimensional-equipped and unequipped, as well as low-and high-performance, aircraft.

Erzberger, H.↗

NASA NTRSDate not supplied

NAS Exploratory Concepts & Technologies (NExCT) Upper Class E Traffic Management (ETM) Collaborative Evaluation #1 (CE-1)

NASA, in partnership with AeroVironment and Aerostar, recently demonstrated a first-of-its-kind air traffic management concept that could pave the way for aircraft to safely operate at higher altitudes. This work seeks to open the door for increased internet coverage, improved disaster response, expanded scientific missions, and even supersonic flight. The concept is referred to as an Upper-Class E traffic management, or ETM. NASA and its partners have developed an ETM traffic management system that allows aircraft to autonomously share location and flight plans, enabling aircraft to stay safely separated. This concept was demonstrated during the recent traffic management simulation in the Airspace Operations Laboratory at Ames, data from multiple air vehicles was displayed across dozens of traffic control monitors and shared with partner computers off site. The study details and the initial results are presented at a regular, informal ETM industry meetings held virtually.

Upper Class E Traffic Management (ETM)↗