Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “air traffic”

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.

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

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Inside the Mechanics of Network Development: How Competition and Strategy Reorganize European Air Traffic

Air transport forms complex networks that can be measured in order to understand its structural characteristics and functional properties. Recent models for network growth (i.e., preferential attachment, etc.) remain stochastic and do not seek to understand other network-specific mechanisms that may account for their development in a more microscopic way. Air traffic is made up of many constituent airlines that are either privately or publicly owned and that operate their own networks. They follow more or less similar business policies each. The way these airline networks organize among themselves into distinct traffic distributions reveals complex interaction among them, which in turn can be aggregated into larger (macro-) traffic distributions. Our approach allows for a more deterministic methodology that will assess the impact of airline strategies on the distinct distributions for air traffic, particularly inside Europe. One key question this paper is seeking to answer is whether there are distinct patterns of preferential attachment for given classes of airline networks to distinct types of European airports. Conclusions about the advancing degree of concentration in this industry and the airline operators that accelerate this process can be drawn.

Huber, Hans↗
NASA NTRS2019

Complex Dynamics of Air Traffic Flow

Air traffic in the United States has continued to grow at a steady pace since 1980, except for a dip immediately after the tragic events of September 11, 2001. There are different growth scenarios associated both with the magnitude and the composition of the future air traffic. The Terminal Area Forecast (TAF), prepared every year by the FAA, projects the growth of traffic in the United States. Both Boeing and Airbus publish market outlooks for air travel annually. Although predicting the future growth of traffic is difficult, there are two significant trends: heavily congested major airports continue to see an increase in traffic, and the emergence of regional jets and other smaller aircraft with fewer passengers operating directly between non-major airports. The interaction between air traffic demand and the ability of the system to provide the necessary airport and airspace resources can be modeled as a network. The size of the resulting network varies depending on the choice of its nodes. It would be useful to understand the properties of this network to guide future design and development. Many questions, such as the growth of delay with increasing traffic demand and impact of the en route weather on future air traffic, require a systematic understanding of the properties of the air traffic network. There has been a major advance in the understanding of the behavior of networks with a large number of components. Several theories have been advanced about the evolution of large biological and engineering networks by authors in diversified disciplines like physics, mathematics, biology and computer science. Several networks exhibit a scale-free property in the sense that the probabilistic distribution of their nodes as a function of connections decreases slower than an exponential. These networks are characterized by the fact that a small number of components have a disproportionate influence on the performance of the network. Scale-free networks are tolerant to random failure of components, but are vulnerable to selective attack on components. This paper examines two network representations for the baseline air traffic system. A network defined with the 40 major airports as nodes and with standard flight routes as links has a characteristic scale: all nodes have 60 or more links and no node has more than 460 links. Another network is defined with baseline aircraft routing structure exhibits an exponentially truncated scale-free behavior. Its degree ranges from 2 connections to 2900 connections, and 225 nodes have more than 250 connections. Furthermore, those high-degree nodes are homogeneously distributed in the airspace. A consequence of this scale-free behavior is that the random loss of a single node has little impact, but the loss of multiple high-degree nodes (such as occurs during major storms in busy airspace) can adversely impact the system. Two future scenarios of air traffic growth are used to predict the growth of air traffic in the United States. It is shown that a three-times growth in the overall traffic may result in a ten-times impact on the density of traffic in certain parts of the United States.

Scale-free Networks↗
NASA NTRSDate not supplied

Evaluation of Initial and Mid-Term Air Traffic Procedures for Urban Air Mobility

Urban air mobility (UAM) operations are expected to expand in scale over the next several years as novel aircraft types, including electric vertical takeoff and landing aircraft, are certified and begin operations. These new aircraft may increase safety, decrease noise, and lower operating costs compared with helicopters, allowing them to operate in ways existing aircraft do not. It is vital that these expanded operations are compatible with and do not disrupt existing operations or the air traffic management system. To study the ways in which scaled UAM operations can best integrate in the national airspace system, NASA and Joby Aviation partnered to conduct a high-fidelity air traffic controller-in-the-loop study. Building on air traffic procedures used to manage high tempo operations in other parts of the airspace, new procedures, routes, and communications protocols were developed and tested by retired controllers in NASA’s Future Flight Central tower simulation facility. In addition, new cooperative airspace constructs in the form of corridors were developed to understand their potential contributions to even greater scales of operation. The controllers managed traffic scenarios in the Dallas-Fort Worth and Dallas Love Field airports consisting of fleets of up to 100 UAM aircraft operating alongside traditional traffic. Metrics for air traffic controller workload, duration of communications, departure delays, and other measures of allowable aircraft throughput were collected. The analysis indicates that using today’s procedures for initial UAM operations under nominal conditions could enable up to 40 operations per hour to an airport’s central terminal area if that involved crossing a runway and up to 55 operations per hour if reaching the central terminal did not involve crossing a runway. Operations at these tempos did not delay or otherwise interfere with simulated runway traffic and were rated acceptable by the air traffic controllers. The new corridor constructs dramatically lowered controller workload in certain circumstances, suggesting they may be effective in further increasing the allowable scale of operations.

Advanced Air Mobility↗
NASA NTRSDate not supplied

Evaluation of Initial and Mid-Term Air Traffic Procedures for Urban Air Mobility Operations

Urban air mobility (UAM) operations are expected to expand in scale over the next several years as novel aircraft types, including electric vertical takeoff and landing aircraft, are certified and begin operations. These new aircraft may increase safety, decrease noise, and lower operating costs compared with helicopters, allowing them to operate in ways existing aircraft do not. It is vital that these expanded operations are compatible with and do not disrupt existing operations or the air traffic management system. To study the ways in which scaled UAM operations can best integrate in the national airspace system, NASA and Joby Aviation partnered to conduct a high-fidelity air traffic controller-in-the-loop study. Building on air traffic procedures used to manage high tempo operations in other parts of the airspace, new procedures, routes, and communications protocols were developed and tested by retired controllers in NASA’s Future Flight Central tower simulation facility. In addition, new cooperative airspace constructs in the form of corridors were developed to understand their potential contributions to even greater scales of operation. The controllers managed traffic scenarios in the Dallas-Fort Worth and Dallas Love Field airports consisting of fleets of up to 100 UAM aircraft operating alongside traditional traffic . Metrics for air traffic controller workload, duration of communications, departure delays, and other measures of allowable aircraft throughput were collected. The analysis indicates that using today’s procedures for initial UAM operations under nominal conditions could enable up to 40 operations per hour to an airport’s central terminal area if that involved crossing a runway and up to 55operations per hour if reaching the central terminal did not involve crossing a runway. Operations at these tempos did not delay or otherwise interfere with simulated runway traffic and were rated acceptable by the air traffic controllers. The new corridor constructs dramatically lowered controller workload in certain circumstances, suggesting they may be effective in further increasing the allowable scale of operations.

Urban Air Mobility↗
NASA NTRS2006

Software for Simulating Air Traffic

Future Air Traffic Management Concepts Evaluation Tool (FACET) is a system of software for performing computational simulations for evaluating advanced concepts of advanced air-traffic management. FACET includes a program that generates a graphical user interface plus programs and databases that implement computational models of weather, airspace, airports, navigation aids, aircraft performance, and aircraft trajectories. Examples of concepts studied by use of FACET include aircraft self-separation for free flight; prediction of air-traffic-controller workload; decision support for direct routing; integration of spacecraft-launch operations into the U.S. national airspace system; and traffic- flow-management using rerouting, metering, and ground delays. Aircraft can be modeled as flying along either flight-plan routes or great-circle routes as they climb, cruise, and descend according to their individual performance models. The FACET software is modular and is written in the Java and C programming languages. The architecture of FACET strikes a balance between flexibility and fidelity; as a consequence, FACET can be used to model systemwide airspace operations over the contiguous U.S., involving as many as 10,000 aircraft, all on a single desktop or laptop computer running any of a variety of operating systems. Two notable applications of FACET include: (1) reroute conformance monitoring algorithms that have been implemented in one of the Federal Aviation Administration s nationally deployed, real-time, operational systems; and (2) the licensing and integration of FACET with the commercially available Flight Explorer, which is an Internet- based, real-time flight-tracking system.

Sridhar, Banavar↗
NASA NTRS2024

Optimizing Air Traffic - Integrating Artificial Intelligence and Machine Learning in Flight Path Planning and 3D Airspace Visualization for Air Traffic Control

Air Traffic Control (ATC) systems are vital components of the National Airspace System (NAS). ATC, Airport Traffic Control Towers (ATCT), and Terminal Radar Approach Control (TRACON) are responsible for directing all flights departing from and arriving at airports, managing our nation’s airspace, preventing potential accidents, and ensuring that every flight is accounted for. However, these systems often face challenges in effectively monitoring the skies. Issues such as poor communication between operators, difficulty in performing operations, and the constant need for vigilance frequently burden ATC operators. Additionally, the projected increase in air traffic in the coming years will only exacerbate the stress associated with this role. To address these issues, we propose a system that assists ATC operators in situations such as handovers, emergencies, and routing aircraft to avoid weather hazards. Our solution includes an Artificial Intelligence (AI) and Machine Learning (ML)-based Flight Pathways Planning System (FPPS) designed to find the fastest and most optimal routes for aircraft, taking into account weather conditions, restricted terrain, and Extended-Range Twin-Engine Operational Performance Standards (ETOPS) ratings. The proposed Predictive Weather Planning Model, included in FPPS, adjusts routes based on real-time and forecasted weather conditions. Additionally, our NVIDIA Omniverse 3D Visualization System offers a highly interactive environment for better visualization and a clear view of the airspace. By incorporating these systems, the roles of ATC, ATCT, and TRACON operators will become more manageable and less stressful, equipping them to efficiently handle the growing density of airspace.

Regina Ayoubi↗
NASA NTRS1993

Advanced air traffic management

Air traffic worldwide continues to grow, and this growth is predicted to continue in the coming decades. Air traffic management (ATM) systems in several parts of the world have now reached their operating limits. The external symptoms of this are increases in the number of delays experienced by the system, and a rise in the frequency of near-misses. If the ATM system fails to develop to provide more capacity, then the result will be a decrease in safety levels, and increasing delays, or a limit on the number of permitted aircraft operations.

Wangermann, J. P.↗
NASA NTRS1978

Precision Positional Data of General Aviation Air Traffic in Terminal Air Space

Three dimensional radar tracks of general aviation air traffic at three uncontrolled airports are considered. Contained are data which describe the position-time histories, other derived parameters, and reference data for the approximately 1200 tracks. All information was correlated such that the date, time, flight number, and runway number match the pattern type, aircraft type, wind, visibility, and cloud conditions.

Melson, W. E., Jr.↗
NASA NTRS2023

Search for UnderUtilized Airspace for Extensible Traffic Management Operations Based on Air Traffic Patterns

This paper presents a new method to facilitate integrating new vehicle traffic operations, operating with existing air traffic operations. The extensible traffic management (xTM) concept assumes that the new vehicles can operate in a dedicated Cooperative Area (CA) with minimal interaction with conventional air traffic and requiring minimal air traffic supervision. Our method assumes that a new xTM CA can be created when an underutilized airspace with little or no traffic can be identified. Our approach involves modeling airspace as a tree data structure and iteratively subdividing it into smaller cells, with underutilized airspace defined as any cells without flight tracks. The benefits of our approach include its applicability to all xTM scenarios, the ability to handle both 2D and 3D space using a unique tree data structure, and computational efficiency for key functions such as space decomposition, labeling of connected cells, and searching of cells containing a given point. By automatically searching for underutilized airspace based on operating air traffic patterns, we can optimize airspace utilization and improve air traffic management. Our proposed approach can quantitatively determine when and where to allow xTM operations in the National Airspace System.

extensible traffic management↗
NASA NTRSDate not supplied

A Framework for Assessment of Autonomy Challenges in Air Traffic Management

Traditionally, air traffic management services have been provided by air traffic controllers and managers stationed in ground facilities, employed or contracted by the public sector, and supported by automation. These centralized, human-centric air traffic management services do not scale to accommodate increasing demands from conventional and new entrant operations for access to the national airspace system. One transformation that provides much needed scalability is increasing the level of autonomy of air traffic management by enabling edge agents of the system, including vehicles, operators, and third-party service suppliers, to collectively self-manage independently from the centralized service providers and enabling the automation to also take on more independent traffic management responsibility from the human agents. This paper identifies challenges to increasing the level of autonomy of air traffic management services. It describes a framework to enable a systematic identification of these challenges. The framework consists of a functional breakdown of air traffic management services and several dimensions characterizing different autonomy scales. The autonomy dimensions include the automation level between human and machine agents, the locus of control between centralized and distributed edge agents, cognitive activities for autonomous situation awareness and decision making, intelligence levels ranging from skill-based to expertise-based autonomous behavior, and uncertainty levels of the dynamics and environment in which autonomous agents operate. Several challenges are identified and categorized using the different dimensions of the autonomy framework.

automation, autonomy framework, collective autonom↗
NASA NTRS2021

Decentralized Control Synthesis for Air Traffic Management in Urban Air Mobility

Urban air mobility (UAM) refers to air transportation services within an urban area, often in an on-demand fashion. We study air traffic management (ATM) for vehicles in a UAM fleet, while guaranteeing system safety requirements such as traffic separation. Existing ATM methods for unmanned aerial systems, such as UAS traffic management, utilize alternative approaches which do not provide strict safety guarantees. No established infrastructure exists for providing ATM at scale for UAM. We provide a decentralized, hierarchical approach for UAM ATM that allows for scalability to high traffic densities as well as providing theoretical guarantees of correctness with respect to user-provided safety specifications. Our main contributions are two-fold. First, we propose a novel UAM ATM architecture that divides the control authority between vertihubs that are each in charge of all UAM vehicles in their local airspace. Each vertihub also contains a number of vertiports that are in charge of UAM vehicle takeoffs and landings. The resulting architecture is decentralized and hierarchical, which not only enables scalability, but also robustness in the event of any individual vertihub or vertiport no longer being operational. Second, we provide a contract-based correct-by-construction reactive synthesis approach that provably guarantees safety properties with respect to user-provided specifications in linear temporal logic. We demonstrate the approach on large-volume UAM air traffic data.

Urban Air Mobility↗
NASA NTRS2024

Evaluation of Initial and Midterm Air Traffic Procedures for Urban Air Mobility Operations

This paper describes a follow-on joint human-in-the loop (HITL) simulation effort by NASA and Joby Aviation that builds on the results of these previous studies. It extends that work by comparing the LOA condition for Initial UAM operations to Midterm operations that includes corridor airspace structures and some other changes to the operating environment. This is the first reported air traffic controller-in-the-loop evaluation of the corridor condition in a high-fidelity simulation environment. The following sections describe the routes, scenarios, and operating conditions along with metrics used to evaluate feasibility from the air traffic controllers’ perspectives. The results section presents the traffic levels that were feasible in each condition and concludes with recommendations for extending the scope and applicability of evaluations like this one in the future.

Savvy Verma↗
NASA NTRS1995

Controlling Air Traffic (Simulated) in the Presence of Automation (CATS PAu) 1995: A Study of Measurement Techniques for Situation Awareness in Air Traffic Control

As automated systems proliferate in aviation systems, human operators are taking on less and less of an active role in the jobs they once performed, often reducing what should be important jobs to tasks barely more complex than monitoring machines. When operators are forced into these roles, they risk slipping into hazardous states of awareness, which can lead to reduced skills, lack of vigilance, and the inability to react quickly and competently when there is a machine failure. Using Air Traffic Control (ATC) as a model, the present study developed tools for conducting tests focusing on levels of automation as they relate to situation awareness. Subjects participated in a two-and-a-half hour experiment that consisted of a training period followed by a simulation of air traffic control similar to the system presently used by the FAA, then an additional simulation employing automated assistance. Through an iterative design process utilizing numerous revisions and three experimental sessions, several measures for situational awareness in a simulated Air Traffic Control System were developed and are prepared for use in future experiments.

French, Jennifer R.↗
NASA NTRS2011

Evaluation of the Monotonic Lagrangian Grid and Lat-Long Grid for Air Traffic Management

The Air Traffic Monotonic Lagrangian Grid (ATMLG) is used to simulate a 24 hour period of air traffic flow in the National Airspace System (NAS). During this time period, there are 41,594 flights over the United States, and the flight plan information (departure and arrival airports and times, and waypoints along the way) are obtained from an Federal Aviation Administration (FAA) Enhanced Traffic Management System (ETMS) dataset. Two simulation procedures are tested and compared: one based on the Monotonic Lagrangian Grid (MLG), and the other based on the stationary Latitude-Longitude (Lat- Long) grid. Simulating one full day of air traffic over the United States required the following amounts of CPU time on a single processor of an SGI Altix: 88 s for the MLG method, and 163 s for the Lat-Long grid method. We present a discussion of the amount of CPU time required for each of the simulation processes (updating aircraft trajectories, sorting, conflict detection and resolution, etc.), and show that the main advantage of the MLG method is that it is a general sorting algorithm that can sort on multiple properties. We discuss how many MLG neighbors must be considered in the separation assurance procedure in order to ensure a five-mile separation buffer between aircraft, and we investigate the effect of removing waypoints from aircraft trajectories. When aircraft choose their own trajectory, there are more flights with shorter duration times and fewer CD&R maneuvers, resulting in significant fuel savings.

Kaplan, Carolyn↗
NASA NTRSDate not supplied

Initial Validation of a Simulation System for Studying Interoperability in Future Air Traffic Management Systems

Future air traffic management systems will need to accommodate large numbers of increasingly diverse air vehicles with different operating paradigms. To support this trend, they will digitally share copious amounts of information via a common communication architecture. Operators will deploy programs that create and negotiate flight plans via the architecture’s communication protocols. These programs will autonomously make decisions that must be arbitrated by the architecture and robust to uncertainty. To study interoperability in air traffic management, a new airspace simulation system was composed by integrating a legacy airspace simulation, an air traffic control model, and a new research communication architecture. It was used to evaluate air traffic management concepts by adapting it to handle congested arrival traffic at Newark Liberty International Airport and executing simulations. Results demonstrated the ability of the simulation system to model in detail strategic traffic flow management, predeparture flight planning, and air traffic control working in concert. Subsequent studies can use the simulation system to study interoperability, autonomy, digital communication, and uncertainty in future air traffic management systems.

aircraft scheduling,traffic flow management,autono↗
NASA NTRS2012

Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

Sridhar, Banavar↗
NASA NTRS2021

Initial Validation of a Simulation System for Studying Interoperability in Future Air Traffic Management Systems

Future air traffic management systems will need to accommodate large numbers of increasingly diverse air vehicles with different operating paradigms. To support this trend, they will digitally share copious amounts of information via a common communication architecture. Operators will deploy programs that create and negotiate flight plans via the architecture’s communication protocols. These programs will autonomously make decisions that must be arbitrated by the architecture and robust to uncertainty. To study interoperability in air traffic management, a new airspace simulation system was composed by integrating a legacy airspace simulation, an air traffic control model, and a new research communication architecture. It was used to evaluate air traffic management concepts by adapting it to handle congested arrival traffic at Newark Liberty International Airport and executing simulations. Results demonstrated the ability of the simulation system to model in detail strategic traffic flow management, predeparture flight planning, and air traffic control working in concert. Subsequent studies can use the simulation system to study interoperability, autonomy, digital communication, and uncertainty in future air traffic management systems.

air traffic control↗
NASA NTRSDate not supplied

Initial Validation of a Simulation System for Studying Interoperability in Future Air Traffic Management Systems

Future air traffic management systems will need to accommodate large numbers of increasingly diverse air vehicles with different operating paradigms. To support this trend, they will digitally share copious amounts of information via a common communication architecture. Operators will deploy programs that create and negotiate flight plans via the architecture’s communication protocols. These programs will autonomously make decisions that must be arbitrated by the architecture and robust to uncertainty. To study interoperability in air traffic management, a new airspace simulation system was composed by integrating a legacy airspace simulation, an air traffic control model, and a new research communication architecture. It was used to evaluate air traffic management concepts by adapting it to handle congested arrival traffic at Newark Liberty International Airport and executing simulations. Results demonstrated the ability of the simulation system to model in detail strategic traffic flow management, predeparture flight planning, and air traffic control working in concert. Subsequent studies can use the simulation system to study interoperability, autonomy, digital communication, and uncertainty in future air traffic management systems.

air traffic control↗