A simulator study of the supersonic transport in the air traffic control system.
Supersonic transport fixed base simulator to anticipate integration problems with air traffic control systems
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Supersonic transport fixed base simulator to anticipate integration problems with air traffic control systems
The effect of airspace factors on air traffic controller (ATC) workload has been an active area of study for almost three decades due to the importance of safety considerations necessary to design and maintain operations. Existing literature has examined several traffic-related (e.g., number of aircraft under control, loss of separation) contributors to ATC workload and proposed mathematical functions to best describe controller response. However, future air traffic continues to increase in complexity with the introduction of urban air mobility (UAM) – or the transportation of humans and cargo using electric vertical takeoff and landing (eVTOL) aircraft. UAM aims to alleviate congestion for existing ground transportation systems and improve mobility within urban centers and other high-demand locations. This shift in the traditional airspace paradigm necessitates an evolved understanding of model use and development for ATC workload prediction. This study aimed to develop an ATC workload forecasting model based on human-in-the-loop (HITL) simulation data for UAM operations at large airports. Data collected from the HITL simulation served as the training and testing data for a Long Short-Term Memory recurrent neural network and enabled time-series forecasting of ATC workload from traffic characteristics. Results demonstrated the potential of LSTM models for forecasting ATC workload 40 minutes into the future and highlighted important considerations for future development.
The effect of airspace factors on air traffic controller (ATC) workload has been an active area of study for almost three decades due to the importance of safety considerations necessary to design and maintain operations. Existing literature has examined several traffic-related (e.g., number of aircraft under control, loss of separation) contributors to ATC workload and proposed mathematical functions to best describe controller response. However, future air traffic continues to increase in complexity with the introduction of urban air mobility (UAM) – or the transportation of humans and cargo using electric vertical takeoff and landing (eVTOL) aircraft. UAM aims to alleviate congestion for existing ground transportation systems and improve mobility within urban centers and other high-demand locations. This shift in the traditional airspace paradigm necessitates an evolved understanding of model use and development for ATC workload prediction. This study aimed to develop an ATC workload forecasting model based on human-in-the-loop (HITL) simulation data for UAM operations at large airports. Data collected from the HITL simulation served as the training and testing data for a Long Short-Term Memory recurrent neural network and enabled time-series forecasting of ATC workload from traffic characteristics. Results demonstrated the potential of LSTM models for forecasting ATC workload 40 minutes into the future and highlighted important considerations for future development.
NASA-FAA simulator program studying integration of SST into air traffic control system with tests of simulated departure and arrival operations
In August 2007, Airservices Australia (Airservices) and the United States National Aeronautics and Space Administration (NASA) conducted a validation experiment of the air traffic control (ATC) procedures associated with the Automatic Dependant Surveillance-Broadcast (ADS-B) In-Trail Procedure (ITP). ITP is an Airborne Traffic Situation Awareness (ATSA) application designed for near-term use in procedural airspace in which ADS-B data are used to facilitate climb and descent maneuvers. NASA and Airservices conducted the experiment in Airservices simulator in Melbourne, Australia. Twelve current operational air traffic controllers participated in the experiment, which identified aspects of the ITP that could be improved (mainly in the communication and controller approval process). Results showed that controllers viewed the ITP as valid and acceptable. This paper describes the experiment design and results.
The document is a set of briefing slides summarizing the work the Advanced Air Transportation Technologies (AATT) Project is doing on predicting air traffic controller and airline pilot human error when using new decision support software tools and when involved in testing new air traffic control concepts. Previous work in this area is reviewed as well as research being done jointly with the FAA. Plans for error prediction work in the AATT Project are discussed. The audience is human factors researchers and aviation psychologists from government and industry.
In the current air traffic management (ATM) system, pilots and air traffic controllers have well-established roles and responsibilities: pilots fly aircraft and are concerned with energy management, fuel efficiency, and passenger comfort; controllers separate aircraft and are concerned with safety and management of traffic flows. Despite having different goals and obligations, both groups must be able to effectively communicate and interact with each other for the ATM system to work. This interaction will become even more challenging as traffic volume increases dramatically in the near future. To accommodate this increase, by 2025 the national air transportation system in the U.S. will go through a transformation that will modernize the ATM system and make it safer, more effective, and more efficient. This new system, NextGen, will change how pilots and controllers perform their tasks by incorporating advanced technologies and employing new procedures. It will also distribute responsibility between pilots, controllers and automation over such tasks as maintaining aircraft separation. The present chapter describes three plausible concepts of operations that allocate different ATM responsibilities to these groups. We describe how each concept changes the role of each operator and the types of decisions and actions performed by them.
Message exchange for air traffic control (ATC) purposes via data link offers the potential benefits of increasing the airspace system safety and efficiency. This is accomplished by reducing communication errors and relieving the overloaded ATC radio frequencies, which hamper efficient message exchanges during peak traffic periods in many busy terminal areas. However, the many uses and advantages of data link create additional questions concerning the interface among the human-users and the cockpit and ground systems. A flight test was conducted in the NASA Langley B-737 airplane to contrast flight operations using current voice communications with the use of data link for transmitting both strategic and tactical ATC clearances during a typical commercial airline flight from takeoff to landing. Commercial airplane pilots were used as test subjects.
Supersonic transport time and fuel problems - relation to air traffic control system
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.
Federal government role in present civil aviation- air traffic control state
Ultrahigh frequency air traffic control satellite simulation experiment using high altitude balloons
Multiple user satellite system for air navigation and traffic control, presenting comparative error analyses for position determination by spherical and hyperbolic ranging
A model of an air traffic controller performing a separation assurance task was produced. The model was designed to be simple to use and deploy in a simulator, but still provide realistic behavior. The model is based upon an evaluation of the safety function of the controller for separation assurance, and utilizes fast and frugal heuristics and belief networks to establish a knowledge set for the controller model. Based on this knowledge set, the controller acts to keep aircraft separated. Validation results are provided to demonstrate the model s performance.
Simulation program for study of problems related to integration of supersonic transport into air traffic control system
Air traffic controllers are responsible for the safety and efficiency of air traffic and therefore must maintain a consistently high standard of performance. However, performance can be negatively affected by factors such as workload and fatigue, potentially leading to performance decline and performance-related incidents. Real-time identification of negative influences would facilitate timely implementation of supportive strategies prior to performance decline. The current study aimed to explore the concept of ‘behavioral indicators’ to identify when a controller was reaching a performance limit. A second aim was to capture behavioral indicators associated with performance influencing factors. A total of 65 controllers spanning Tower, Approach and Enroute facilities across the United States of America were interviewed. Findings revealed that controllers were familiar with the concept of behavioral indicators, and that indicators were associated with specific performance-influencing factors. Implications for implementing behavioral indicators training in control environments are discussed.
The air transportation system is on the verge of gridlock, with delays and cancelled flights this summer reaching all time highs. As demand for air transportation continues to increase, the capacity needed to accommodate the growth in traffic is falling farther and farther behind. Moreover, it has become increasingly apparent that the present system cannot be scaled up to provide the capacity increases needed to meet demand over the next 25 years. NASA, working with the Federal Aviation Administration and industry, is pursuing a major research program to develop air traffic management technologies that have the ultimate goal of doubling capacity while increasing safety and efficiency. This seminar will describe how the current system operates, what its limitations are and why a revolutionary "shift in paradigm" is needed to overcome fundamental limitations in capacity and safety. For the near term, NASA has developed a portfolio of software tools for air traffic controllers, called the Center-TRACON Automation System (CTAS), that provides modest gains in capacity and efficiency while staying within the current paradigm. The outline of a concept for the long term, with a deployment date of 2015 at the earliest, has recently been formulated and presented by NASA to a select group of industry and government stakeholders. Automated decision making software, combined with an Internet in the sky that enables sharing of information and distributes control between the cockpit and the ground, is key to this concept. However, its most revolutionary feature is a fundamental change in the roles and responsibilities assigned to air traffic controllers.
Report describes study of Descent Advisor algorithm: software automation aid intended to assist air-traffic controllers in spacing traffic and meeting specified times or arrival. Based partly on mathematical models of weather conditions and performances of aircraft, it generates suggested clearances, including top-of-descent points and speed-profile data to attain objectives. Study focused on operational characteristics with specific attention to how it can be used for prediction, spacing, and metering.