HEMA - a Robust, Computational Architecture for Modeling Human Error

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-03-M-0357
Agency Tracking Number: N031-0221
Amount: $69,967.00
Phase: Phase I
Program: SBIR
Awards Year: 2003
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
1000 Technology Drive, Suite 3220, Fairmont, WV, 26554
DUNS: 606180883
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Michael Fotta
 Principal Investigator
 (304) 363-6757
Business Contact
 Beth Gribble
Title: VP - Finance & Contracts
Phone: (304) 363-6757
Email: beth.gribble@dnamerican.com
Research Institution
The growing use of sensors and other data-generating devices increases the chance of operator error. This is especially true of cutting-edge weapons systems, where the human operator must receive, process and act on an increasingly-complex array ofinformation from numerous sources. Human error in these systems can lead to serious and even deadly consequences. A tool that can help predict the occurrence of these errors early in the system design process would be extremely valuable to both systemdesigners and the human operators of these systems. Such a predictive tool would assist the system designers to minimize both the incidence and severity of human errors. D.N. American proposes the development of this predictive, human error modelingtool. The Phase I team brings substantial expertise in cognitive psychology, cognitive architectures, simulations, genetic algorithms and parallel programming to this approach. This combination of expertise will ensure the success of this innovativehuman error modeling tool. The initial target end users of this software tool will be current suppliers of information systems, software/hardware systems, etc. to the Department of Defense. However, the trend of increasing the amount, speed and formatof data delivered to human operators is evident in numerous civilian applications. Examples include air traffic control operators, manufacturing control centers, automobiles, call centers, etc. In each of these examples, the proposed human error modelingsystem will help reduce the incidence and severity of human errors. Consequently, the proposed technology will prove valuable to designers of system that involve human/machine interface in these civilian applications as well.

* information listed above is at the time of submission.

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