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Details of Grant 

EPSRC Reference: GR/S66985/01
Title: Adaptive Control of Automation in Human-Machine Systems through Operator Functional State Monitoring
Principal Investigator: Hockey, Professor GRJ
Other Investigators:
Mahfouf, Professor M
Researcher Co-Investigators:
Professor DA Linkens
Project Partners:
TNO Institute for Human Factors
Department: Psychology
Organisation: University of Sheffield
Scheme: Standard Research (Pre-FEC)
Starts: 01 October 2004 Ends: 31 March 2008 Value (£): 377,407
EPSRC Research Topic Classifications:
Human-Computer Interactions
EPSRC Industrial Sector Classifications:
Transport Systems and Vehicles
Related Grants:
Panel History:  
Summary on Grant Application Form
A dilemma for the design of automation is that human operators are either kept 'out of the loop' by excessive automation or, when human-centred designs are used, vulnerable to performance breakdown under environmental stress and high workload. A solution is proposed through the application of adaptive automation (AA), in which task functions are switched dynamically from human to computer when vulnerable (physiological and behavioural) states are detected in the operator. This is made difficult, however, by the operator's use of compensatory strategies, which normally prevent manifest breakdown in performance, but give rise to strain states. Accordingly, a new 'cyclic loading' technique is proposed, in which load is systematically increased until breakdown occurs, allowing determination of the critical pre-breakdown strain state. The approach is to carry out intensive testing in individual operators on a simulated process control task, with monitoring of key brain and bodily responses. The obtained data will then be modelled using neuro-fuzzy logic methods, and an intelligent adaptive interface developed for implementation in the simulation. To optimise effectiveness the proposed architecture will include both common and individual-specific components. Testing and validation of the AA design will be carried out on both the process control simulation and an advanced flight simulator, and outcomes assessed against a set of critical predictions.
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Organisation Website: http://www.shef.ac.uk