Adaptive Interface for Management of Bias and Workload Reduction (AMBR) Navy SBIR FY2005.2 Sol No.: Navy SBIR FY2005.2 Topic No.: N05-109 Topic Title: Adaptive Interface for Management of Bias and Workload Reduction (AMBR) Proposal No.: N052-109-0151 Firm: Charles River Analytics Inc. 625 Mount Auburn Street Cambridge, Massachusetts 02138-4555 Contact: Karen Harper Phone: (617) 491-3474 Web Site: www.cra.com Abstract: Advances in aircraft performance and weapons capability have led to a dramatic increase in the tempo of tactical situations facing the combat aviator or UAV controller, reducing the operator's available information processing and decision-making time and resources. Furthermore, the technological and information advances of Network Centric Warfare (NCW) have resulted in an explosion in the complexity and sheer quantity of information that is available to the operator. To counter this increasingly complex operational environment, the Navy requires advanced human/system interface concepts that will make optimal use of the operator's cognitive resources and minimize potential for operator error. The adaptive interface should enhance the flow of information and control between the operator and the vehicle to improve the operator's situation awareness (SA) and decision-making performance while alleviating workload and reducing the effects of cognitive biases, and thus improving survivability, lethality, and ultimately, mission effectiveness. To address this need, we propose to develop a prototype Adaptive Interface for Management of Bias and Workload Reduction (AMBR) that uses computational SA models, operator mental and physical state tracking, and cognitive bias tracking to drive the content, format, and modality of military displays for operation of advanced aviation systems. Benefits: The proposed technology has considerable potential for improving the link between human operator and machine in the military aviation system, especially in closed crew stations, where the operator does not have a direct visual link with the outside world. The technology is also applicable to commercial and general aviation systems, especially in the coming era of Distributed Air/Ground Traffic Management (DAG-TM) where traffic awareness must be maintained by aircraft crews. Adaptive interfaces, SA technologies, and human state and bias recognition offer potential in other high-value operator/system environments, including power system control rooms and process control centers. Return