A Closed-Loop Adaptive System for Command and Control

On Navy ships, technological developments enable crews to work more efficiently and effectively. However, in such complex, autonomous, and information-rich environments a competition for the users' attention is going on between different information items, possibly leading to a cognitive overload. This overload originates in the limitations of human attention and constitutes a well-known and well-studied bottleneck in human information processing. The concept of adaptive automation promises a solution to the overwhelmed operator by shifting the amount of work between the human and the system in time, while maintaining a high level of situation awareness. One of the most critical challenges in developing adaptive human-machine collaboration concerns the design of a trigger mechanism. This paper discusses and evaluates a number of possible triggers for the usage in closed-loop adaptive automation from the perspective of command and control.

[1]  Claude E. Shannon,et al.  A Mathematical Theory of Communications , 1948 .

[2]  Mustapha Mouloua,et al.  Effects of Adaptive Task Allocation on Monitoring of Automated Systems , 1996, Hum. Factors.

[3]  J. M. Peter,et al.  The Efficacy of Psychophysiological Measures for Implementing Adaptive Technology , 2001 .

[4]  David B. Kaber,et al.  The effects of level of automation and adaptive automation on human performance, situation awareness and workload in a dynamic control task , 2004 .

[5]  P A Hancock,et al.  Pilot performance and preference for short cycles of automation in adaptive function allocation. , 1995, Applied ergonomics.

[6]  E. S. Conklin,et al.  A Comparison of the Scale of Values Method with the Order-of-Merit Method. , 1923 .

[7]  Mark W. Scerbo,et al.  Comparison of a Brain-Based Adaptive System and a Manual Adaptable System for Invoking Automation , 2006, Hum. Factors.

[8]  N. Moray,et al.  Adaptive automation, trust, and self-confidence in fault management of time-critical tasks. , 2000, Journal of experimental psychology. Applied.

[9]  Mustapha Mouloua,et al.  Automation and Human Performance : Theory and Applications , 1996 .

[10]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[11]  B. Rouse William,et al.  Adaptive Aiding for Human/Computer Control , 1988 .

[12]  E. Hollnagel Handbook of Cognitive Task Design , 2009 .

[13]  Jefferson M. Koonce,et al.  Human–automation interaction: Research and practice. , 1997 .

[14]  Toshiyuki Inagaki Situation-Adaptive Autonomy for Time-Critical Takeoff Decisions , 2000 .

[15]  J. A. Veltman,et al.  The Role of Operator State Assessment in Adaptive Automation , 2005 .