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All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Life-Cycle Cost/Benefit Assessment of Expedite Departure Path (EDP)

This report presents a life-cycle cost/benefit assessment (LCCBA) of Expedite Departure Path (EDP), an air traffic control Decision Support Tool (DST) currently under development at NASA. This assessment is an update of a previous study performed by bd Systems, Inc. (bd) during FY01, with the following revisions: The life-cycle cost assessment methodology developed by bd for the previous study was refined and calibrated using Free Flight Phase 1 (FFP1) cost information for Traffic Management Advisor (TMA, or TMA-SC in the FAA's terminology). Adjustments were also made to the site selection and deployment scheduling methodology to include airspace complexity as a factor. This technique was also applied to the benefit extrapolation methodology to better estimate potential benefits for other years, and at other sites. This study employed a new benefit estimating methodology because bd s previous single year potential benefit assessment of EDP used unrealistic assumptions that resulted in optimistic estimates. This methodology uses an air traffic simulation approach to reasonably predict the impacts from the implementation of EDP. The results of the costs and benefits analyses were then integrated into a life-cycle cost/benefit assessment.

Wang, Jianzhong Jay↗
NASA NTRS2009

An Exploratory Study of Runway Arrival Procedures: Time Based Arrival and Self-Spacing

The ability of a flight crew to deliver their aircraft to its arrival runway on time is important to the overall efficiency of the National Airspace System (NAS). Over the past several years, the NAS has been stressed almost to its limits resulting in problems such as airport congestion, flight delay, and flight cancellation to reach levels that have never been seen before in the NAS. It is predicted that this situation will worsen by the year 2025, due to an anticipated increase in air traffic operations to one-and-a-half to three times its current level. Improved arrival efficiency, in terms of both capacity and environmental impact, is an important part of improving NAS operations. One way to improve the arrival performance of an aircraft is to enable the flight crew to precisely deliver their aircraft to a specified point at either a specified time or specified interval relative to another aircraft. This gives the flight crew more control to make the necessary adjustments to their aircraft s performance with less tactical control from the controller; it may also decrease the controller s workload. Two approaches to precise time navigation have been proposed: Time-Based Arrivals (e.g., required times of arrival) and Self-Spacing. Time-Based Arrivals make use of an aircraft s Flight Management System (FMS) to deliver the aircraft to the runway threshold at a given time. Self-Spacing enables the flight crew to achieve an ATC assigned spacing goals at the runway threshold relative to another aircraft. The Joint Planning and Development Office (JPDO), a multi-agency initiative established to plan and coordinate the development of the Next Generation Air Transportation System (NextGen), has asked for data for both of these concepts to facilitate future research and development. This paper provides a first look at the delivery performance of these two concepts under various initial and environmental conditions in an air traffic simulation environment.

Houston, Vincent E.↗
NASA NTRS2010

Analysis of Different Cost Functions in the Geosect Airspace Partitioning Tool

A new cost function representing air traffic controller workload is implemented in the Geosect airspace partitioning tool. Geosect currently uses a combination of aircraft count and dwell time to select optimal airspace partitions that balance controller workload. This is referred to as the aircraft count/dwell time hybrid cost function. The new cost function is based on Simplified Dynamic Density, a measure of different aspects of air traffic controller workload. Three sectorizations are compared. These are the current sectorization, Geosect's sectorization based on the aircraft count/dwell time hybrid cost function, and Geosect s sectorization based on the Simplified Dynamic Density cost function. Each sectorization is evaluated for maximum and average workload along with workload balance using the Simplified Dynamic Density as the workload measure. In addition, the Airspace Concept Evaluation System, a nationwide air traffic simulator, is used to determine the capacity and delay incurred by each sectorization. The sectorization resulting from the Simplified Dynamic Density cost function had a lower maximum workload measure than the other sectorizations, and the sectorization based on the combination of aircraft count and dwell time did a better job of balancing workload and balancing capacity. However, the current sectorization had the lowest average workload, highest sector capacity, and the least system delay.

Wong, Gregory L.↗
NASA NTRS1993

Pseudo Aircraft Systems - A multi-aircraft simulation system for air traffic control research

Pseudo Aircraft Systems (PAS) is a computerized flight dynamics and piloting system designed to provide a high fidelity multi-aircraft real-time simulation environment to support Air Traffic Control research. PAS is composed of three major software components that run on a network of computer workstations. Functionality is distributed among these components to allow the system to execute fast enough to support real-time operation. PAS workstations are linked by an Ethernet Local Area Network, and standard UNIX socket protocol is used for data transfer. Each component of PAS is controlled and operated using a custom designed Graphical User Interface. Each of these is composed of multiple windows, and many of the windows and sub-windows are used in several of the components. Aircraft models and piloting logic are sophisticated and realistic and provide complex maneuvering and navigational capabilities. PAS will continually be enhanced with new features and improved capabilities to support ongoing and future Air Traffic Control system development.

Weske, Reid A.↗
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 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↗
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 NTRS2014

Evolutionary Agent-Based Simulation of the Introduction of New Technologies in Air Traffic Management

Accurate simulation of the effects of integrating new technologies into a complex system is critical to the modernization of our antiquated air traffic system, where there exist many layers of interacting procedures, controls, and automation all designed to cooperate with human operators. Additions of even simple new technologies may result in unexpected emergent behavior due to complex human/ machine interactions. One approach is to create high-fidelity human models coming from the field of human factors that can simulate a rich set of behaviors. However, such models are difficult to produce, especially to show unexpected emergent behavior coming from many human operators interacting simultaneously within a complex system. Instead of engineering complex human models, we directly model the emergent behavior by evolving goal directed agents, representing human users. Using evolution we can predict how the agent representing the human user reacts given his/her goals. In this paradigm, each autonomous agent in a system pursues individual goals, and the behavior of the system emerges from the interactions, foreseen or unforeseen, between the agents/actors. We show that this method reflects the integration of new technologies in a historical case, and apply the same methodology for a possible future technology.

Simulation↗
NASA NTRS1998

A Distributed Simulation Facility to Support Human Factors Research in Advanced Air Transportation Technology

A distributed real-time simulation of the civil air traffic environment developed to support human factors research in advanced air transportation technology is presented. The distributed environment is based on a custom simulation architecture designed for simplicity and flexibility in human experiments. Standard Internet protocols are used to create the distributed environment, linking all advanced cockpit simulator, all Air Traffic Control simulator, and a pseudo-aircraft control and simulation management station. The pseudo-aircraft control station also functions as a scenario design tool for coordinating human factors experiments. This station incorporates a pseudo-pilot interface designed to reduce workload for human operators piloting multiple aircraft simultaneously in real time. The application of this distributed simulation facility to support a study of the effect of shared information (via air-ground datalink) on pilot/controller shared situation awareness and re-route negotiation is also presented.

Amonlirdviman, Keith↗
NASA NTRS1989

Piloted simulation of a ground-based time-control concept for air traffic control

A joint simulation was carried out using a piloted simulator and an advanced-concept air traffic control simulation to study the acceptability and accuracy of the ground-based four-dimensional descent advisor (DA), an automation aid based on accurate models of aircraft performance and weather conditions. In the piloted simulation, airline crews executed controller-issued descent advisories along standard curved-path arrival routes and were able to achieve an arrival-time precision of plus or minus 20 s at the metering fix. An analysis of errors generated in turns resulted in a further enhancement of the DA algorithm.

Davis, Thomas J.↗
NASA NTRSDate not supplied

A Simulation Architecture for Air Traffic Over Urban Environments Supporting Autonomy Research in Advanced Air Mobility

As part of its research, NASA investigates concepts, aircraft, and operations related to Advanced Air Mobility (AAM). One of the most challenging scenarios for AAM will be enabling safe routine access near densely populated urban centers. AAM flight operations over a regional area require a moderately high-fidelity simulation capability to develop and evaluate autonomy technologies in the urban environment. This paper aims to describe a system to simulate flight operations around regions such as the San Francisco-Oakland Bay area at a moderately-high scale (tens to hundreds of flights) that incorporates detailed vehicle models and control necessary to support research in airborne autonomy. The flight vehicle utilizes NASA AAM concept vehicle dynamics integrated with a custom flight management system and flight control system to simulate all flight phases accurately. The simulation incorporates a detailed simulated urban environment and includes glass cockpit displays to monitor aircraft operations. Simulation models integrate to simulate air and ground-based sensors, such as Radar and LiDAR. As a commercially available rendering engine, X-Plane 11 is used as the renderer to simulate vision-based sensors (such as onboard and ground-based cameras) with a detailed graphical model of a city at different times of the day and weather conditions. This paper presents the simulation and software architecture used for simulating AAM traffic over this urban region. This system enables the evaluation of NASA research concepts in autonomy for urban AAM operations on the path toward flight test evaluation.

distributed sensing↗
NASA NTRSDate not supplied

A Simulation Architecture for Air Traffic Over Urban Environments Supporting Autonomy Research in Advanced Air Mobility

As part of its research, NASA investigates concepts, aircraft, and operations related to Advanced Air Mobility (AAM). One of the most challenging scenarios for AAM will be enabling safe routine access near densely populated urban centers. AAM flight operations over a regional area require a moderately high-fidelity simulation capability to develop and evaluate autonomy technologies in the urban environment. This paper aims to describe a system to simulate flight operations around regions such as the San Francisco-Oakland Bay area at a moderately-high scale (tens to hundreds of flights) that incorporates detailed vehicle models and control necessary to support research in airborne autonomy. The flight vehicle utilizes NASA AAM concept vehicle dynamics integrated with a custom flight management system and flight control system to simulate all flight phases accurately. The simulation incorporates a detailed simulated urban environment and includes glass cockpit displays to monitor aircraft operations. Simulation models integrate to simulate air and ground-based sensors, such as Radar and LiDAR. As a commercially available rendering engine, X-Plane 11 is used as the renderer to simulate vision-based sensors (such as onboard and ground-based cameras) with a detailed graphical model of a city at different times of the day and weather conditions. This paper presents the simulation and software architecture used for simulating AAM traffic over this urban region. This system enables the evaluation of NASA research concepts in autonomy for urban AAM operations on the path toward flight test evaluation.

Distributed sensing↗
NASA NTRSDate not supplied

A Simulation Architecture for Air Traffic Over Urban Environments Supporting Autonomy Research in Advanced Air Mobility

NASA is conducting investigations into Advanced Air Mobility (AAM) concepts, aircraft, and operations. One of the most challenging scenarios for AAM will be enabling safe routine access into densely populated urban centers. To address challenges in the urban environment, a moderately high-fidelity simulation capability is needed to investigate AAM flight operations over a regional area for the development and evaluation of autonomy technologies. This paper describes a system to simulate flight operations around regions such as the San Francisco-Oakland Bay area at a moderately-high scale (10's-100's of flights) that incorporates detailed vehicle models and control necessary to support research in airborne autonomy. The flight vehicle utilizes NASA AAM concept vehicle dynamics integrated with a custom flight management system and flight control system to accurately simulate all phases of flight. Glass cockpit displays have been developed for monitoring aircraft operation over a detailed simulated urban environment. Simulation models have been integrated to simulate air and ground-based sensors, such as radar and LIDAR. The commercial X-Plane software package is used as a rendering engine to mimic vision-based sensors (such as onboard and ground-based cameras) at various times of day and in various weather conditions over a relatively detailed graphical model of the city. The paper presents a detailed illustration of the simulation and software architecture used for traffic over this urban region. This system is enabling the evaluation of NASA research concepts in autonomy for urban AAM operations on the path toward aircraft flight test evaluation.

Keerthana Kannan↗
NASA NTRS1983

A simulation study of crew performance in operating an advanced transport aircraft in an automated terminal area environment

A simulation study assessing crew performance operating an advanced transport aircraft in an automated terminal area environment is described. The linking together of the Langley Advanced Transport Operating Systems Aft Flight Deck Simulator with the Terminal Area Air Traffic Model Simulation was required. The realism of an air traffic control (ATC) environment with audio controller instructions for the flight crews and the capability of inserting a live aircraft into the terminal area model to interact with computer generated aircraft was provided. Crew performance using the advanced displays and two separate control systems (automatic and manual) in flying area navigation routes in the automated ATC environment was assessed. Although the crews did not perform as well using the manual control system, their performances were within acceptable operational limits with little increase in workload. The crews favored using the manual control system and felt they were more alert and aware of their environment when using it.

Houck, J. A.↗