Title

The Utility Of Adaptive Automation In Intelligence, Surveillance, And Reconnaissance Operations

Abstract

The Intelligence, Surveillance and Reconnaissance (ISR) missions require much attention from the operator to identify changes in the environment, detect threats, and relay information. The longer time spent on task, the more diligent the operator must be. However, vigilance literature shows that operator performance deteriorates over time, known as the vigilance decrement, and rate of decline is greater with more demanding tasks. ISR operations are multi-tasking environments and thus induce higher levels of stress and workload in the operator, often associated with a reduction in performance. The goal is to identify the solution for optimized stress, workload, and performance. Adaptive automation is the proposed answer. Adaptive automation is expected to mitigate the negative effects caused by a sustained attention, multi-tasking assignment. Adaptive automation refers to a system capability designed for sharing work cooperatively with a human. In so doing, the human is maintained in-the-loop and maximum human-machine potential is achieved within the working environment. An ISR simulated environment was developed, requiring participants to identify intelligence updates symbolized by a change detection task using military icons, detect threats in route, respond verbally to radio communications. Participants drove the Unmanned Ground Vehicle (UGV) using a joystick through a designated route displayed on the screen or monitored the UGV as it autonomously was guided through the mission via waypoints. Adaptive scenarios were those in which both modes of control were implemented throughout 24 minute missions, dependent upon workload evoked by the change detection task (number of icons changed, rate of change, and number of icons in view). The benefit of such research is effectively employing a system capability to reduce operator stress and improve performance, ultimately saving lives.

Publication Date

12-1-2011

Publication Title

AUVSI Unmanned Systems North America Conference 2011

Volume

1

Number of Pages

11-22

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

84857270756 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84857270756

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