ATC, Air Traffic Control

Note. HCI = human-computer interaction ATC = air traffic control Type = type of study F = field S = simulation L = laboratory. 

Note. HCI= human-computer interaction HR = heart rate ATC = air traffic control. 

Modeling or simulating automation systems and the behavior of human operators in aircraft or in ATC (Air Traffic Control) (e.g. Inoue et al. (2010) present a model of knowledge in ATC operations, Yemelyanov (2009) introduces a complex method for modeling operator performance and analyzing error)... 

Investigator Yeah, when you go to apply take-off power, but that s the last defence, so if that s not working then the aircraft ain t flying. Or it ll fly for a bit but then not fly. They re saying here ATC [Air Traffic Control] asked them to change runway. Bullshit, they re meant to be working through the checklist items and they clearly haven t. We need to get to the bottom of it. (S14-6)... 

Several studies have examined the total sleep times obtained by air traffic controllers (ATC) in different settings. In one Federal Aviation Administration (FAA) study of shift schedules, results showed that controllers averaged about 8 hr of sleep prior to an afternoon or midday shift (20) and about 7.5 hr of sleep before a day shift. The study also showed that controllers obtained a total of about... 

In a study of workload and stress among 18 military air traffic controllers (ATCs), Wientjes, ter Maat, and Gaillard (1994) employed a special purpose ambulatory 8-channel digital physiological recorder (see Wientjes, Spiekman, Benschop, Hoogeweg, 1994) in addition to paper-and-pencil questioimaires and observational methods. On the basis of extensive consultation of ATC experts, two workload measures were collected that were hypothesized to reflect two distinct aspects of the demand characteristics of the ATC task (a) the number of aircraft that were simultaneously under control per time unit, and (b) the number of potential conflict situations per time unit (i.e., when, mostly due to miscommunication, an aircraft under control was potentially in conflict with another aircraft and special measures were necessary to prevent accidents). 

During the interview a case study was identified that describes an incident where, due to the mistake of a pilot of one taxiing aircraft, two aircraft were taking off almost simultaneously from crossing runways. After the correct intervention of the air traffic controllers from the ATC Tower, and adequate decision making, coordination and action of the pilots of one of the aircraft, a collision was prevented. This incident is described (in an anonymised manner) in the following section. 

Figure 7.2 shows the high-level requirements and constraints for some of the air traffic control hazards identified above. Comparing the ATC high-level constraints with the TCAS high-level constraints (figure 7.3) is instructive. Ground-based air traffic control has additional requirements and constraints related to aspects of the collision problem that TCAS cannot handle alone, as well as other hazards and potential aircraft accidents that it must control. 

TCAS was intended to be an independent backup to the normal Air Traffic Control (ATC) system and the pilot s see and avoid responsibilities. It interrogates air traffic control transponders on aircraft in its vicinity and listens for the transponder replies. By analyzing these rephes with respect to slant range and relative altitude, TCAS determines which aircraft represent potential collision threats and provides appropriate display indications, called advisories, to the flight crew to assure proper... 

Air Traffic Control Maintain separation between aircraft in the controlled airspace by providing advisories (control actions) for the pilot to follow. TCAS is designed to be independent of and a backup for the air traffic controller so ATC does not have a direct role in the TCAS safety control structure but clearly has an indirect one. 

A different type of coordination problem occurred in an aircraft collision near Uberlingen, Germany, in 2002 [28, 212], The two controllers—the automated onboard TCAS system and the ground air traffic controller—provided uncoordinated control instructions that conflicted and actually caused a collision. The loss would have been prevented if both pilots had followed their TCAS alerts or both had followed the ground ATC instructions. 

Along with increasing air traffic demands in the near future, we can predict that burdens on Air Traffic Control (ATC) will also increase. Prevention of human errors in ATC is therefore becoming a key issue for safe and reliable air transportation. In this situation, cognitive aspects of ATC have not yet been studied sufficiently and no consistent measures for performance assessment of ATC have been established, either. 

Besides the natural enviromnent, since the very beginning of aviation the flight safety has been strongly affected by artificial enviromnent. This is a man-made infrastmcture composed of objects that provide capabilities to perform flights. Exemplary objects/systems of this kind are air traffic control (ATC) facilities, runways, navigational aids, landing systems, other aircraft. 

ABSTRACT The tasks involved in air traffic control (ATC) make heavy demands on the information processing capacities of air traffic controllers. In particular, human factors problems that lead to both major and minor incidents are considered to be a serious problem for ATC in air traffic safety. Since ATC is usually undertaken by a team of controllers, team collaboration is a key issue for keeping good condition in ATC. However, this aspect has not been well studied compared with individual cognitive process. In this research, we examined the functional problems in an ATC system from the human factors aspects, and concluded that a systematic method and models are needed to analyze this problem. Thus, we consider that an effective way to understand user requirements is to analyze user tasks based on actual field data. The aim of this research is to analyze team cognitive processes and team situation awareness in normal (i.e., not accidental) situations for a team of en route air traffic controllers based on the distributed cognition approach so as to better understand current ATC systems. 

Air traffic control (ATC) is a complex process that depends to a large degree on human capabilities. ATC systems of the future are e q)ected to change to the concept based on Air Traffic Management (ATM). In ATM, air traffic controllers (ATCo) wiU continue to play an important role in the future systems. This is indicated in the concept of next generation ATM such as SESAR and NextGen. 

Here we describe the cognitive model of an air traffic controller from the observation. We observed that there are some specific features in the work of ATC, in particular, the basis of work is prediction and instruction to secure and maintain a safe traffic situation. As for the radar controller in en route control tasks, the controller predicts the traffic between five to ten minutes ahead. Meanwhile the coordination controller elaborates the... 

Inoue, S., Kanno, T, Aoyama, H. Fumta, K. 2007. Task Analysis of Air Traffic Controllers in En-Route ATC. In Proc. 14thlnt Symp. on Aviation Psychology, Dayton OH. 

Svww.aopa.org/News-and-Video/AU-News/2014/November/06/ATC-Zero-Inside-the-Chicago-Center-fire www.npr.org/2014/09/29/352538409/chicago-air-traffic-control-fire-still-disrupting-flights-days-later www.faa.gov/news/press releases/news stary. cfm newsld=17834... 

FREQUENTIS is a producer of voice and data communication systems in many different areas like air traffic control (ATC), public transport, maritime and public safety. Our customers are spread around the world. Most of our products are used for safety related or critical tasks. Therefore our customers often demand or need a safety case, partly to be allowed by the authorities to go live with their system. 

One example of a data-driven application are Air Traffic Control (ATC) systems that use data in several forms, a static description of the airspace and the aircraft (including its capabilities and capacities), dynamic data to represent the instantaneous position of the aircraft in flight, a command schedule (a set of flight plans) to describe the intended use of the system and data representing the current operational conditions (such as weather conditions) which may constrain the use of the system. 

The radios that comprise the avionics of an aircraft include communications radios that pilots use to talk to air traffic control (ATC) and other aircraft and navigation radios. Early navigation radios relied on ground-based radio signals, but many aircraft have come to use GPS receivers that receive their information from satellites. Other components of an aircraft s avionics include a transponder, which sends a discrete code to ATG to identify the aircraft and is used in the military to discern ftiendly and enemy aircraft, and radar, which is used to locate rain and thunderstorms and to determine the aircraft s height above the ground. 

Assessing the human operator within his/her task, envirorunental and organizational systems has never been more important than in the present increasingly technological age. Air Traffic Control (ATC) is one domain where the importance of HF has been grasped with both hands. 

At approximately 10 minutes before the top of descent, Air Traffic Control (ATC) issues a change of weather conditions for Melbourne. 

In our present study, we introduced a functional relationship diagram showing technical and human subsystems affecting air traffic safety at ATC side, then we focused on the human operators in the system of ATC and their impact on the safety (and efficiency) of air traffic. We examined the factors that influence the workload of air traffic controllers working in the Flight Information Region (FIR) of Budapest (BUD) and analyzed how different sets of such factors can be used to predict the optimal number of controllers needed to handle a certain traffic situation. 

In an attempt to enhance the safety of air traffic control in Hungarian airspace, we conducted a study to examine the possibility of using a neural network model as a basis for a supervisory decision support tool that would be able to estimate the optimal number of ATC sectors for a given traffic situation based on its complexity. Data about the importance of different complexity parameters was gathered using a simple method that focused on finding out the subjective opinions of ATC experts. To validate our method, we used neural network calculations with different sets of complexity parameters. 

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