The Relationship Between Workload and Performance in Air Traffic Control: Exploring the Influence of Levels of Automation and Variation in Task Demand

Abstract

Abstract.In an air traffic environment, task demand is dynamic. However, previous research has largely considered the association of task demand and controller performance using conditions of stable task demand. Further, there is a comparatively restricted understanding of the influence of task demand transitions on workload and performance in association with different types and levels of automation that are available to controllers. This study used an air traffic control simulation to investigate the influence of task demand transitions, and two conditions of automation, on workload and efficiency-related performance. Findings showed that both the direction of the task demand variation and the amount of automation influenced the relationship between workload and performance. Findings are discussed in relation to capacity and arousal theories. Further research is needed to enhance understanding of demand transition and workload history effects on operator experience and performance, in both air traffic control and other safety-critical domains.

Effects of coherent, integrated, and context-dependent adaptable user interfaces on operators’ situation awareness, performance, and workload

“…While SA could be improved by working harder, high mental workload can negatively affect operators' SA (Endsley 1995;Vidulich and Tsang 2012). A low cognitive task load on the other hand can result in boredom and under-load, which also may negatively affect SA assessment and task performance (Edwards et al 2017). SA knowledge is the understanding of dynamic information associated with operator' goals and does not include more static knowledge stored in long-term memory (Endsley 2000).…”

“…It is the human-machine interaction that determines which information is essential for operators' SA (Van Doorn et al 2017b). This makes it difficult to predict or understand the effect of automation, such as implemented in the context-dependent adaptable UI, on operator's performance (Edwards et al 2017;Parasuraman and Riley 1997). SA is also influenced by the design of interfaces and the type of information provisioned by the machine during interaction.…”

On the Use of Machine Learning for EEG-Based Workload Assessment: Algorithms Comparison in a Realistic Task

“…In fact, air traffic controllers are continuously engaged in visual activities (airplane control on the radar) and auditory (as they communicate with the pilots of different aircrafts). The ATM represents one of the fields where the evaluation of workload has a fundamental role both in training aspects and in operational conditions [48], [49]. In fact, it has been established that it is a high demanding work during which the slightest error could have very ominous effects [50].…”

Mental Workload in the Explanation of Automation Effects on ATC Performance

“…Air traffic control (ATC) has all the characteristics of a complex and dynamic task: there are many elements (aircrafts and obstacles) that are interconnected; all these elements are changing constantly due to both the actions of the air traffic controller (ATCo) and their own dynamics; some of the variables are not transparent to the ATCo; and the objective is to direct all aircraft traffic safely and orderly at the same time. For this reason, it has been indicated that the mental workload of the ATCo is related to the complexity of the ATC system [11,12]. A great deal of theoretical and applied research has been directed over the years to reducing the complexity of the ATCo task and, thus, to make it safer and less uncertain.…”