Air Traffic Managers Research Articles

Using random forests to diagnose aviation turbulence.

Atmospheric turbulence poses a significant hazard to aviation, with severe encounters costing airlines millions of dollars per year in compensation, aircraft damage, and delays due to required post-event inspections and repairs. Moreover, attempts to avoid turbulent airspace cause flight delays and en route deviations that increase air traffic controller workload, disrupt schedules of air crews and passengers and use extra fuel. For these reasons, the Federal Aviation Administration and the National Aeronautics and Space Administration have funded the development of automated turbulence detection, diagnosis and forecasting products. This paper describes a methodology for fusing data from diverse sources and producing a real-time diagnosis of turbulence associated with thunderstorms, a significant cause of weather delays and turbulence encounters that is not well-addressed by current turbulence forecasts. The data fusion algorithm is trained using a retrospective dataset that includes objective turbulence reports from commercial aircraft and collocated predictor data. It is evaluated on an independent test set using several performance metrics including receiver operating characteristic curves, which are used for FAA turbulence product evaluations prior to their deployment. A prototype implementation fuses data from Doppler radar, geostationary satellites, a lightning detection network and a numerical weather prediction model to produce deterministic and probabilistic turbulence assessments suitable for use by air traffic managers, dispatchers and pilots. The algorithm is scheduled to be operationally implemented at the National Weather Service’s Aviation Weather Center in 2014.

Causal simulation models for facing third millennium air transport sustainability

Aeronautics and air transport is a vital sector of our society and economy. Air transport logistics is one of the key players to support efficient globalization; however, sustainable mobility is at stake, due to facts such as the interdependencies with the financial system, climate change and an increasing scarcity of resources. This paper highlights the consequences of a lack of a proper understanding of air-side and land-side, leading to an unsustainable air transport system. A system approach for knowledge sharing between air traffic controllers, handling operators, airlines and airport managers is justified by means of causal models to design a mitigation mechanism to tackle perturbations instead of increasing the latent capacity. The simulation benefits to design indicators of sustainability are also mentioned.

Human–Systems Integration Design Process of the Air Traffic Control Tower Flight Data Manager

A user-friendly system that yields operational benefit results from data-driven prototype evaluations and benefits analyses that iteratively feed back into the prototype design and development. In this study, initial requirements development and field evaluations were conducted using a shadow operations technique at the center tower backup Dallas–Fort Worth International Airport air traffic control tower (ATCT). Results are discussed in reference to the design process of the Tower Flight Data Manager (TFDM) prototype. Nonintrusive measures for quantitatively validating human–systems design issues were identified for this study, including visual gaze analysis and verbal command sequence analysis. Behavioral validation of design issues simplifies the process to prioritize beneficial design changes. The iterative process used resulted in an interim TFDM prototype that was rated by active air traffic controllers as both beneficial and usable in an operational ATCT environment.

Human Factors at the Federal Aviation Administration (FAA): From Research to Reality

The purpose of this discussion panel is to inform human factors researchers and practitioners of the role of human factors throughout the Federal Aviation Administration (FAA) and how the FAA uses human factors research to enhance aviation safety and to support the performance of the national airspace system. Through this panel, the FAA hopes to provide outreach by communicating the Agency’s research needs and requirements to help researchers and practitioners facilitate the transition from research and development to tangible outcomes for the public. This panel will describe the role of the FAA Human Factors Division in coordinating human factors research at the Agency, the process for how research projects are initiated at the FAA, and the challenges faced in transitioning results to implementation in the field or in regulation. Two examples of research programs (Electronic Flight Bag and the Air Traffic Front Line Manager (FLM) Quick Reference Guide) that were successfully implemented are discussed.

A Field Demonstration of the Air Traffic Control Tower Flight Data Manager Prototype

The development and evaluation process of the Tower Flight Data Manager prototype at Dallas Ft. Worth airport is described. Key results from the first field evaluation are presented, including lessons learned about making electronic flight information acceptable to controllers. Iteration of the field evaluation methods are discussed for practitioner benefit.

Assessing the Human Contribution to Risk in NextGen

In an effort to modernize the National Airspace System, the Federal Aviation Administration has introduced the Next Generation Air Transportation System (NextGen). The introduction of new systems and procedures as described in NextGen offers the potential for significant changes to the daily activities of air traffic controllers. Each change presents the opportunity for both positive and negative effects on the overall safety of the NAS and the role of the air traffic manager. This paper presents a methodology for prospectively identifying hazards to the performance of air traffic controllers as well as a summary of the categorization of the hazards by task. Scenarios describing NextGen airport departure operations and operations with varying levels of equipage presented the most significant human performance hazards. These identified hazards represent rich opportunities for future human factors research.

Computing Aircraft Position Prediction~!2008-08-05~!2008-10-18~!2008-11-28~!

Air traffic is increasing world wide at a steady annual rate, and airport congestion is already a major issue for air traffic managers. This paper presents a model based on neural networks to predict the position of aircraft on the airport, during landing or takeoff. The same model can also be used to predict the behavior of other vehicles moving on the airport. The predictions help to detect near-collision situations earlier, giving air traffic controllers additional time to take remedial actions. The system uses the list of coordinates produced by the airport radar system, and obtains a prediction of the future position of each object. It is only necessary to store a short history of positions for each object in order to perform the estimation. This estimation has an average error comparable to the size of the airplane when the algorithm is adjusted for 20 second look ahead. The proposed model has been evaluated using data from Chicago O’Hare International Airport, which is the airport with the highest number of movements (from 2001 to 2004).

Seasonal Sensitivity on COBEL-ISBA Local Forecast System for Fog and Low Clouds

Skillful low visibility forecasts are essential for air-traffic managers to effectively regulate traffic and to optimize air-traffic control at international airports. For this purpose, the COBEL-ISBA local numerical forecast system has been implemented at Paris CDG international airport. This local approach is robust owing to the assimilation of detailed local observations. However, even with dedicated observations and initialization, uncertainties remain in both initial conditions and mesoscale forcings. The goal of the research presented here is to address the sensitivity of COBEL-ISBA forecast to initial conditions and mesoscale forcings during the winter season 2002-2003. The main sources of uncertainty of COBEL-ISBA input parameters have been estimated and the evaluation of parameter uncertainty on the forecasts has been studied. A budget strategy is applied during the winter season to quantify COBEL-ISBA sensitivity. This study is the first step toward building a local ensemble prediction system based on COBEL-ISBA. The conclusions of this work point out the potential for COBEL-ISBA ensemble forecasting and quantify sources of uncertainty that lead to dispersion. Accurate prediction of fog and low clouds is one of the main issues related to improving air-traffic management and safety. At Paris Charles de Gaulle (CdG) international airport, adverse ceiling and visibility conditions (visibility under 600 m and ceiling below 60 m) lead to the application of Low Visibility Procedures (LVP). Under these conditions, the airport take-off/landing efficiency is reduced by a factor of 2, causing aircraft delays. In this context, accurate short-term forecasts of LVP conditions are considered to be a priority by airport authorities. Unfortunately, current operational Numerical Weather Prediction (NWP) models are not able to provide detailed information due to their lack of both vertical and horizontal resolutions with respect to the typical length scale of fog. However, owing to higher vertical resolution and more detailed physics than 3D

Rapid Prototyping of Airport Advanced Operational Systems and Procedures through Distributed Simulation

Despite the recent crisis in civil aviation, most agree that air traffic growth will soon recover and rise even further. To meet the expected airport demand and improve efficiency of ground operations while maintaining safety, several new operational systems and procedures are being tested and evaluated. Rapid prototyping through modeling and simulation remains a well-suited approach to meet evaluation and assessment requirements. Likewise, simulation is increasingly part of the decision support tools used by both air and ground traffic managers and the airline industry for short-term decision making. Within this context, the French Aeronautics and Space Research Center is designing a set of modeling and simulation tools for rapid prototyping of advanced operational systems and procedures. The main goal of this initiative is to develop an open, scalable, and reusable simulation architecture, facilitating both integration of additional components and interoperability between them, to evaluate and compare several airport configurations.

Demonstration of the Surface Management System: An Air Traffic Control Decision Support Tool

The Surface Management System (SMS) is an information and decision support tool designed for use by air traffic (AT) controllers and traffic managers. Developed by NASA and the FAA, the goals of SMS are to: 1) provide information and decision support for tactical and strategic air traffic control tasks to increase situational awareness of surface operations through knowledge of current and future demand; 2) maximize airport throughput and minimize surface delays by increasing efficiency and coordinating arrival and departure management; and 3) assist FAA controllers and traffic managers in handling surface operations by predicting and displaying future demand. To reach these goals, SMS provides flight-specific and aggregate demand and delay information on display interfaces including map displays, timelines, load graphs, and flight and status tables. The information presented on these displays and the display format has evolved through human factors demonstrations and evaluations during the SMS human-centered development process.

Enhancements to the FAA Ground-Delay Program Under Collaborative Decision Making

When airport arrival capacity is reduced, it may not meet the demand placed by arriving aircraft. In these cases, the FAA enacts a ground-delay program (GDP) to delay flights before they depart from their origin airports, keeping traffic at an acceptable level for the affected arrival airport. However, air-traffic managers sometimes lacked current data and a common situational awareness when running a GDP. Working with the FAA and the airline community, Metron, Inc. and Volpe National Transportation Systems Center improved the process by using real-time data exchange between all users, new algorithms to assign flight-arrival slots, and new software at FAA facilities and airlines. This paper reflects the views and opinions of the authors and does not necessarily reflect that of the FAA.

Future air traffic management: technology, operations, and human factors implications

The NASA, the FAA and Eurocontrol have initiated programs of research and development to provide flight crew, air line operators and air traffic managers with automation aids to increase capacity in enroute and terminal areas, to support the goals of safe, flexible, predictable and efficient operations, and to ensure, and to enhance the safety of operations in the response to demands for capacity enhancement. Achievement of these goals is enabled by increased precision of knowledge of aircraft and asset position in space and time, by increased density and bandwidth of transmitted information among the airspace assets and users, and by increased service and information to the flight deck, ATC and airline operations centers. These aiding technologies are intended to support exploitation of timely and dynamic information on atmospheric hazards, traffic fluctuations, and airspace utilization. These systems are intended to support the human operators who maintain the authority and responsibility for safe, efficient operations through cognitive aiding technologies, to serve as cognitive orthoses (Reason, 1988) [12].

Information Manager for Determining Data Presentation Preferences in Future Enroute Air Traffic Management

One proposed vision of the future National Airspace System (NAS) involves a change in philosophy from that of air traffic control to one of air traffic management, i.e. Free Flight. In order to accommodate this philosophy change, new technologies will be implemented to assist the air traffic manager (today's air traffic controller) in decision making. When enhancing the system we must also consider the interface between the air traffic manager and this new system and its corresponding new philosophy. To better determine the design of such an interface we must first understand the information needs of the air traffic manager. The present study investigated the information requirements of 58 enroute air traffic controllers. The controllers provided their preferences in presentation frequency as well as the importance of the information to be displayed. The results reveal the potential for adaptive automation as a form of information management.

Cognitive Performance for Multiple Operators in Complex Dynamic Airspace Systems: Computational Representation and Empirical Analyses

This paper presents a set of studies in full mission simulation and the development of a predictive computational model of human performance in control of complex airspace operations. NASA and the FAA have initiated programs of research and development to provide flight crew, airline operations and air traffic managers with automation aids to increase capacity in enroute and terminal area to support the goals of safe, flexible, predictable and efficient operations. In support of these developments, we present a computational model to aid design that includes representation of multiple cognitive agents (both human operators and intelligent aiding systems). The demands of air traffic management require representation of many intelligent agents sharing world-models, coordinating action/intention, and scheduling goals and actions in a potentially unpredictable world of operations. The operator-model structure includes attention functions, action priority, and situation assessment. The cognitive model has been expanded to include working memory operations including retrieval from long-term store, and interference. The operator's activity structures have been developed to provide for anticipation through knowledge of the intention and action of remote operators. System stability and operator actions can be predicted by using the model. The model's predictive accuracy was verified using the full-mission simulation data of commercial flight deck operations with advanced air traffic management techniques.

Symposium: Decision Making in Free Flight

In its web-page introduction to free flight, the Federal Aviation Administration (FAA) describes free flight as “an innovative concept to improve the efficiency of the National Airspace System [in which] pilots operating under instrument flight rules will be able to select the aircraft's course, speed, and altitude in real time” (FAA, 1996). This symposium presents the results of experimental and theoretic investigations on (1) the ability of pilots and air traffic managers to master the demands of free flight and (2) the design of technology and decision aids tailored to need those demands.

Resource Management in the Highly Automated Airspace System

The introduction of highly sophisticated, glass cockpit aircraft has profoundly affected the flightdeck environment, and has changed the nature of crew resource management (CRM). CRM and decision making in advanced aircraft are qualitatively different from the same processes in older fleets. Automation also alters the nature of interaction among crewmembers, and between crewmembers and Air Traffic Control (ATC) These differences would seem to necessitate special training and procedures for CRM in glass cockpits. Moreover, training for managing automation cannot be merely an added module in current CRM programs. The effects of automation pervade throughout all aspects of resource management. Coincidentally, advances in the air traffic control system are altering the modern airspace environment. In the not-too-distant future, it will be possible for ATC computers to generate or amend clearances, which the Air Traffic Manager will send to the aircraft via datalink. The aircraft FMS (flight management system) will determine whether or not the clearance may be accepted, and its effects on fuel consumption, arrival time, etc. The role of the pilot will be to accept or reject the suggested clearance. The effects of automation on operator and team processes in both of these domains, as well as on the interaction between the domains, has only begun to be defined. Some of the issues already raised in the flightdeck realm, such as diffusion of responsibility among crewmembers, the breakdown of traditional roles and responsibilities as a result of familiarity with automation, or the possibility that crewmembers will “communicate” more with the automation than with each other, may only be exacerbated by increased automation in the air-ground communication link. The goal of this panel is to present an overview of some of the issues and questions to be resolved if resource management is to be a vital construct in the highly automated airspace system. To open discussion, the first panel member will present an overview of the general issues involved in the confluence of CRM and automation. Following, an industry representative will discuss one airline's specialized program to introduce crewmembers to the glass cockpit, and guide them in the appropriate use of automation. The measurement of CRM components specifically related to crew interaction with automation will be the focus of the third panelist. The analysis of CRM issues associated with equipment design, and, in particular, with the introduction of datalink communication systems, will be the next panel topic. Lastly, possible implications for human operators of the increasing sophistication and decision-making capabilities of automated systems in the air and on the ground will be introduced. The panel chair will summarize the major points and propose questions for discussion.

The Gust-Front Detection and Wind-Shift Algorithms for the Terminal Doppler Weather Radar System

The Federal Aviation Administration's Terminal Doppler Weather Radar (TDWR) system was primarily designed to address the operational needs of pilots in the avoidance of low-altitude wind shears upon takeoff and landing at airports. One of the primary methods of wind-shear detection for the TDWR system is the gust-front detection algorithm. The algorithm is designed to detect gust fronts that produce a wind-shear hazard and/or sustained wind shifts. It serves the hazard warning function by providing an estimate of the wind-speed gain for aircraft penetrating the gust front. The gust-front detection and wind-shift algorithms together serve a planning function by providing forecasted gust-front locations and estimates of the horizontal wind vector behind the front, respectively. This information is used by air traffic managers to determine arrival and departure runway configurations and aircraft movements to minimize the impact of wind shifts on airport capacity. This paper describes the gust-front detection and wind-shift algorithms to be fielded in the initial TDWR systems. Results of a quantitative performance evaluation using Doppler radar data collected during TDWR operational demonstrations at the Denver, Kansas City, and Orlando airports are presented. The algorithms were found to be operationally useful by the FAA airport controllers and supervisors.

Aerospace Education vs. Aviation and Space Education

There are many different organizations involved in developing programs and teaching materials which use aviation and space concepts in education. These entities include governmental agencies, private industry, aviation and space associations and lobbying groups, and private non-profit organizations. Each of them has a different vested interest in aviation and space, and therefore each has a different idea about what aviation and space education really is. Also, each uses different terminology for their programs. Some are called aviation education, while others use terminology such as air age education, aeronautical education, aviation science, space science education, aeronautics and space education, air and space education, aerospace technology, and aerospace education. Is it any wonder that the ultimate users of these programs--the education community--are confused about what aviation and space education is really all about? These aviation and space education programs have almost as many goals and objectives as there are organizations involved in them. Some are designed to use aviation and space concepts to help teach traditional school subjects. Others have a goal of preparing pilots, astronauts, air traffic controllers, airport managers, or professionals for other aerospace related fields. Still others look at using a youngster's interest in aviation and space as a way to improve the math and science skills of the student. All of these are worthwhile goals, and there is a place for each of these programs in education today.

Nowcasts of Thunderstorm Initiation and Evolution

Abstract This paper reports on experimental space-specific 30-min nowcasts of thunderstorm initiation, evolution, and movement. The experiments were conducted near Denver, Colorado, with the purpose of providing weather information for planning purposes to air traffic control managers. The nowcasts were based primarily on Doppler weather radar observations of the clear-air boundary layer, storm reflectivity, storm Doppler velocity structure, and visual observations of clouds. The forecasters found that they could often anticipate thunderstorm initiation by monitoring radar-detected boundary-layer convergence lines together with monitoring visual observations of cloud development in the vicinity of the convergence lines. Nowcast procedures and nowcast results for experiments in 1989 and 1990 are presented. The procedures are based on research experiments and exploratory field tests conducted since 1984. The forecaster results were better than persistence or extrapolation forecasts because of the ability to...