This paper addresses theoretical, empirical, and analytical studies pertaining to human use, misuse, disuse, and abuse of automation technology. Use refers to the voluntary activation or disengagement of automation by human operators. Trust, mental workload, and risk can influence automation use, but interactions between factors and large individual differences make prediction of automation use difficult. Misuse refers to over reliance on automation, which can result in failures of monitoring or decision biases. Factors affecting the monitoring of automation include workload, automation reliability and consistency, and the saliency of automation state indicators. Disuse, or the neglect or underutilization of automation, is commonly caused by alarms that activate falsely. This often occurs because the base rate of the condition to be detected is not considered in setting the trade-off between false alarms and omissions. Automation abuse, or the automation of functions by designers and implementation by man...

Humans and automation: Use, misuse, disuse, abuse

Approach motivation is the energization of behavior by, or the direction of behavior toward, positive stimuli (objects, events, possibilities), whereas avoidance motivation is the energization of behavior by, or the direction of behavior away from, negative stimuli (objects, events, possibilities). In this article, I provide a brief overview of this distinction between approach and avoidance motivation. In addition, I provide a brief overview of a model of motivation in which this approach-avoidance distinction plays an integral role—the hierarchical model of approach-avoidance motivation.

The Hierarchical Model of Approach-Avoidance Motivation

Objective: We perform a critical review of research on mental workload in en route air traffic control (ATC). We present a model of operator strategic behavior and workload management through which workload can be predicted within ATC and other complex work systems. Background: Air traffic volume is increasing worldwide. If air traffic management organizations are to meet future demand safely, better models of controller workload are needed. Method: We present the theoretical model and then review investigations of how effectively traffic factors, airspace factors, and operational constraints predict controller workload. Results: Although task demand has a strong relationship with workload, evidence suggests that the relationship depends on the capacity of the controllers to select priorities, manage their cognitive resources, and regulate their own performance. We review research on strategies employed by controllers to minimize the control activity and information-processing requirements of control tasks. Conclusion: Controller workload will not be effectively modeled until controllers' strategies for regulating the cognitive impact of task demand have been modeled. Application: Actual and potential applications of our conclusions include a reorientation of workload modeling in complex work systems to capture the dynamic and adaptive nature of the operator's work. Models based around workload regulation may be more useful in helping management organizations adapt to future control regimens in complex work systems.

Modeling and Predicting Mental Workload in En Route Air Traffic Control: Critical Review and Broader Implications

This paper describes our exploration of a design space for an augmented reality prototype. We began by observing air traffic controllers and their interactions with paper flight strips. We then worked with a multi-disciplinary team of researchers and controllers over a period of a year to brainstorm and prototype ideas for enhancing paper flight strips, We argue that augmented reality is more promising (and simpler to implement) than the current strategies that seek to replace flight strips with keyboard/monitor interfaces. We also argue that an exploration of the design space, with active participation from the controllers, is essential not only for designing particular artifacts, but also for understanding the strengths and limitations of augmented reality in general.

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Reinventing the familiar: exploring an augmented reality design space for air traffic control

The characterization of complex air traffic situations is an important issue in air traffic management (ATM) Within the current ground-based ATM system, complexity metrics have been introduced with the goal of evaluating the difficulty experienced by air traffic controllers in guaranteeing the appropriate aircraft separation in a sector The rapid increase in air travel demand calls for new generation ATM systems that can safely and efficiently handle higher levels of traffic To this purpose, part of the responsibility for separation maintenance will be delegated to the aircraft, and trajectory management functions will be further automated and distributed The evolution toward an autonomous aircraft framework envisages new tasks where assessing complexity may be valuable and requires a whole new perspective in the definition of suitable complexity metrics This paper presents a critical analysis of the existing approaches for modeling and predicting air traffic complexity, examining their portability to autonomous ATM systems Possible applications and related requirements will be discussed

R Weston

Papers

Human factors in air traffic control