Bi-weekly Report, July 8, 1949

Bi-weekly progress report of the Air Traffic Control Project team

Bi-weekly Report, July 22, 1949

Bi-weekly progress report of the Air Traffic Control Project team

Bi-weekly Report, January 6, 1950

Bi-weekly progress report of the Air Traffic Control Project team

Application of fuel/time minimization techniques to route planning and trajectory optimization

Rising fuel costs combined with other economic pressures have resulted in industry requirements for more efficient air traffic control and airborne operations. NASA has responded with an on-going research program to investigate the requirements and benefits of using new airborne guidance and pilot procedures that are compatible with advanced air traffic control systems and that will result in more fuel efficient flight. The results of flight testing an airborne computer algorithm designed to provide either open-loop or closed-loop guidance for fuel efficient descents while satisfying time constraints imposed by the air traffic control system is summarized. Some of the potential cost and fuel savings that are obtained with sophisticated vertical path optimization capabilities are described

Air Traffic Control

Improving air traffic control and air traffic management is currently one of the top priorities of the global research and development agenda. Massive, multi-billion euro programs like SESAR (Single European Sky ATM Research) in Europe and NextGen (Next Generation Air Transportation System) in the United States are on their way to create an air transportation system that meets the demands of the future. Air traffic control is a multi-disciplinary field that attracts the attention of many researchers, ranging from pure mathematicians to human factors specialists, and even in the legal and financial domains the optimization and control of air transport is extensively studied. This book, by no means intended to be a basic, formal introduction to the field, for which other textbooks are available, includes nine chapters that demonstrate the multi-disciplinary character of the air traffic control domain

Inverse Optimal Planning for Air Traffic Control

We envision a system that concisely describes the rules of air traffic control, assists human operators and supports dense autonomous air traffic around commercial airports. We develop a method to learn the rules of air traffic control from real data as a cost function via maximum entropy inverse reinforcement learning. This cost function is used as a penalty for a search-based motion planning method that discretizes both the control and the state space. We illustrate the methodology by showing that our approach can learn to imitate the airport arrival routes and separation rules of dense commercial air traffic. The resulting trajectories are shown to be safe, feasible, and efficient

Automatic speech recognition in air traffic control

Automatic Speech Recognition (ASR) technology and its application to the Air Traffic Control system are described. The advantages of applying ASR to Air Traffic Control, as well as criteria for choosing a suitable ASR system are presented. Results from previous research and directions for future work at the Flight Transportation Laboratory are outlined

Air Traffic Control Safety Indicators: What is Achievable?

European Air Traffic Control is extremely safe. The drawback to this safety record is that it is very difficult to estimate what the ‘underlying’ accident rate for mid-air collisions is now, or to detect any changes over time. The aim is to see if it possible to construct simple ATC safety indicators that correlate with this underlying accident rate. A perfect indicator would be simple to comprehend and capable of being calculated by a checklist process. An important concept is that of ‘system control’: the ability to determine the outcome against reasonably foreseen changes and variations of system parameters. A promising indicator is ‘Incident Not Resolved by ATC’, INRA, incidents in which the ground ATC defences have been ‘used up’. The key question is: if someone says he or she knows how to make a good estimate of the underlying accident rate, then how could this claim be tested? If it correlates very well with INRA, then what would be the argument for saying that it is a better indicator

Human factors aspects of air traffic control

An overview of human factors problems associated with the operation of present and future air traffic control systems is presented. A description is included of those activities and tasks performed by air traffic controllers at each operational position within the present system. Judgemental data obtained from controllers concerning psychological dimensions related to these tasks and activities are also presented. The analysis includes consideration of psychophysiological dimensions of human performance. The role of the human controller in present air traffic control systems and his predicted role in future systems is described, particularly as that role changes as the result of the system's evolution towards a more automated configuration. Special attention is directed towards problems of staffing, training, and system operation. A series of ten specific research and development projects are recommended and suggested work plans for their implementation are included