Adaptive Automation: Sharing and Trading of Control

Abstract

Function allocation is the design decision to determine which functions are to be performed by humans and which are to be performed by machines to achieve the required system goals, and it is closely related to the issue of automation. Some of the traditional strategies of function allocation include (a) assigning each function to the most capable agent (either human or machine), (b) allocating to machine every function that can be automated, and (c) finding an allocation scheme that ensures economical efficiency. However, such "who does what" decisions are not always appropriate from human factors viewpoints. This chapter clarifies why "who does what and when" considerations are necessary, and it explains the concept of adaptive automation in which the control of functions shifts between humans and machines dynamically, depending on environmental factors, operator workload, and performance. Who decides when the control of function must be shifted? That is one of the most crucial issues in adaptive automation. Letting the computer be in authority may conflict with the principle of human-centered automation which claims that the human must be maintained as the final authority over the automation. Qualitative discussions cannot solve the authority problem. This chapter proves the need for quantitative investigations with mathematical models, simulations, and experiments for a better understanding of the authority issue.Starting with the concept of function allocation, this chapter describes how the concept of adaptive automation was invented. The concept of levels of automation is used to explain interactions between humans and machines. Sharing and trading are distinguished to clarify the types of human-automation collaboration. Algorithms for implementing adaptive automation are categorized into three groups, and comparisons are made among them. Benefits and costs of adaptive automation, in relation to decision authority, trust-related issues, and human-interface design, are discussed with some examples.

Task Switching and Single vs. Multiple Alarms for Supervisory Control of Multiple Robots

“…Under extreme stress or time pressured tasks, humans tend to defer to automation and rely on the system for making decisions [15]. This increased compliance under high workload could be especially beneficial to system performance where optimal strategies such as SJF can be used to steer operator attention.…”

“…Operators in the Open-queue condition missed the most victims (15) and FIFO the fewest (11) with SJF falling in between (13). A repeated measures ANOVA shows a main effect among queue conditions, F(2,58)=20.5, p<.001.…”

In Praise of Abundance: Why Individuals Matter in Design Science

“…In the implicit control mode, the machine decides which LOA is the most appropriate; in the explicit mode, this decision is under the jurisdiction of the human. Overall, when compared to static automation, there seem to be benefits of adaptive automation with regard to operator performance, including reductions in mental workload, although there is a considerable degree of inconsistency in the literature (e.g., Inagaki, 2003;Kaber & Riley, 1999;. The work featured here is drawn from long-term programme of research on adaptable automation involving colleagues at the university of Fribourg, Switzerland.…”

Allocation of functions in a far-term air traffic control environment

“…A subsequent allocation of certain functions to the automation previously limited to human operators can then occur, but not without substantial forethought. A great deal of research has gone into the area of function allocation between humans and automation that has spanned a number of domains [1][2][3][4]. Air traffic control is certainly no exception [5][6][7][8].…”