Adaptive aiding for human/computer control

TL;DR: Understanding the factors associated with each of these aspects of human use of automation can lead to improved system design, effective training methods, and judicious policies and procedures involving automation use.

TL;DR: In this paper, the authors address theoretical, empirical, and analytical studies pertaining to human use, misuse, disuse, and abuse of automation technology, and propose a method to detect false alarms and omissions.

TL;DR: The effect of variations in the reliability of an automated monitoring system on human operator detection of automation failures was examined in two experiments, providing the first empirical evidence of the performance consequences of these changes.

TL;DR: In this paper, the authors extended previous research on two approaches to human-centred automation: intermediate levels of automation (LOAs) for maintaining operator involvement in complex systems control and facilitating situation awareness; and adaptive automation (AA) for managing operator workload through dynamic control allocations between the human and machine over time.

TL;DR: The role of the human operator as a problem solver in man-machine systems such as vehicles, process plants, transportation networks, etc. is considered and specifications for an overall model outlined.

TL;DR: The conceptual design of a comprehensive support system for operators of complex systems is presented, and a variety of difficult design issues are discussed, and ongoing efforts aimed at resolving these issues are noted.

TL;DR: Queueing theory is employed to model this dynamic approach to the allocation of responsibility between human and computer in multitask decisionmaking situations and results of simulation experiments are used to illustrate the effects of several system variables.

TL;DR: Computers in Organizational Settings and Organizational Demands and Stress.