Air traffic complexity indicators &amp; ATC sectors classification

Raphael, Christien; Benkouar, A.; Chaboud, Thomas; Loubières, P.

doi:10.1109/dasc.2002.1067924

Cited by 16 publications

(11 citation statements)

References 4 publications

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“…Complexity is not a synonym for workload, although it has been proven multiple times that the increase in complexity results in increase in workload which in turn limits the airspace sector capacity [14,15]. Mogford et al [11] reviewed numerous research articles in search of complexity and workload relationship.…”

Section: Air Traffic Complexity 21 Definition and Purposementioning

confidence: 99%

Air Traffic Complexity as a Source of Risk in ATM

Radišić¹,

Andraši²,

Novák³

et al. 2020

Risk Assessment in Air Traffic Management

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In this chapter the connection between air traffic complexity and risks in air traffic management system will be explored. Air traffic complexity is often defined as difficulty of controlling a traffic situation, and it is therefore one of the drivers for air traffic controller's workload. With more workload, the probability of air traffic controller committing an error increases, so it is necessary to be able to assess and manage air traffic complexity. Here, we will give a brief overview of air traffic complexity assessment methods, and we will put the traffic complexity assessment problem into a broader context of decision complexity. Human reliability assessment methods relevant to air traffic management will be presented and used to assess the risk of loss of separation in traffic situations with different levels of complexity. To determine the validity of the human reliability assessment method, an analysis of conflict risk will be made based on the real-time human-in-the-loop (HITL) simulations.On the other hand, Cilliers, in his seminal book on the topic, claims exactly the opposite [6]:If a system-despite the fact that it may consist of a huge number of components-can be given a complete description in terms of its individual constituents, such a system is merely complicated. [...] In a complex system, on the other hand, the interaction among constituents of the system, and the interaction between the 3 Air Traffic Complexity as a Source of Risk in ATM DOI: http://dx.doi.org/10.5772/intechopen.90310 system and its environment, are of such a nature that the system as a whole cannot be fully understood simply by analysing its components.

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Section: Air Traffic Complexity 21 Definition and Purposementioning

confidence: 99%

Air Traffic Complexity as a Source of Risk in ATM

Radišić¹,

Andraši²,

Novák³

et al. 2020

Risk Assessment in Air Traffic Management

View full text Add to dashboard Cite

show abstract

“…Pawlak et al (1996), for instance, viewed planning, monitoring, and evaluating as the primary processes that are dependent on mental effort. Researchers also have distinguished between static factors and dynamic ones (Rodgers, Mogford, & Mogford, 1998), and they have found that dynamic factors can be either flight related or interaction related (Christien, Benkouar, Chaboud, & Loubieres, 2003).…”

Section: An Environmental and Behavioral Look At Workloadmentioning

confidence: 99%

Air Traffic Control

Durso¹,

Manning²

2008

Reviews of Human Factors and Ergonomics

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Determining how the controller (or air navigation service provider) of the future will function in tomorrow's Next Generation Air Transportation System (NextGen) will require an understanding of the existing literature. In this chapter, after an analysis of the controller's job, we focus on technology, which is an important factor in air traffic control (ATC) today and will become increasingly so in NextGen. We then turn to workload and the extent to which it can be predicted. From human-technology interaction and workload, we move to the multiple facets of cognition thought to underlie these and other aspects of the controller's job. Beyond individual cognition, we review collaboration among controllers and discuss both synchronous cooperation and the cooperative shift change. As we move up the system, we look at error, risk, and safety. Finally, we consider the work on controller selection, covering both "select-in" (KSAOs) and "select-out" (e.g., medical and suitability) factors. For NextGen to be successful, human factors researchers must determine from today's research how the human operator can best function to provide ATC services in the future.

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“…However, since different types of interactions have different levels of difficulty in resolving them and interactions can be directly or indirectly related and connected, it is wrong to equate the number of interactions directly with complexity. It is also wrong to equate air traffic complexity and workload, although it has been proven that the increase in complexity results in the increase in workload which is the limiting factor of airspace sector capacity [2,3]. Mogford et al [4] reviewed many research papers searching for relationship between complexity and workload.…”

Section: Introductionmentioning

confidence: 99%

Subjective Air Traffic Complexity Estimation Using Artificial Neural Networks

Andraši¹,

Radišić²,

Novák³

et al. 2019

PROMET

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Air traffic complexity is usually defined as difficulty of monitoring and managing a specific air traffic situation. Since it is a psychological construct, best measure of complexity is that given by air traffic controllers. However, there is a need to make a method for complexity estimation which can be used without constant controller input. So far, mostly linear models were used. Here, the possibility of using artificial neural networks for complexity estimation is explored. Genetic algorithm has been used to search for the best artificial neural network configuration. The conclusion is that the artificial neural networks perform as well as linear models and that the remaining error in complexity estimation can only be explained as inter-rater or intra-rater unreliability. One advantage of artificial neural networks in comparison to linear models is that the data do not have to be filtered based on the concept of operations (conventional vs. trajectory-based).

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Air traffic complexity indicators & ATC sectors classification

Cited by 16 publications

References 4 publications

Air Traffic Complexity as a Source of Risk in ATM

Air Traffic Complexity as a Source of Risk in ATM

Air Traffic Control

Subjective Air Traffic Complexity Estimation Using Artificial Neural Networks

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