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Operators Context and Trust in Automation Visualization (OCTAV) Tool

Award Information
Agency: Department of Defense
Branch: Office of the Secretary of Defense
Contract: FA8651-14-M-0111
Agency Tracking Number: O133-HS5-1111
Amount: $149,994.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: OSD13-HS5
Solicitation Number: 2013.3
Solicitation Year: 2013
Award Year: 2014
Award Start Date (Proposal Award Date): 2014-07-09
Award End Date (Contract End Date): 2015-04-08
Small Business Information
9180 Brown Deer Road
San Diego, CA -
United States
DUNS: 131182388
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Heather Oonk
 Senior Scientist
 (858) 535-1661
Business Contact
 James Callan
Title: President
Phone: (858) 535-1661
Research Institution

Pacific Science & Engineering Group (PSE) proposes to design, develop, and demonstrate a prototype human-autonomous system tool & #208;Operators Context and Trust in Automation Visualization (OCTAV) & #208; that will support improved transparency, trust, and human-machine team performance. OCTAV will automatically monitor human and autonomous system team context and task, visualize context-based status, and make recommendations regarding the appropriateness of the team task allocation. The content of the tool will be based on knowledge gained through interactions with subject matter experts in the unmanned systems community and on the findings within the human-autonomy literature. PSE will build upon an already-developed understanding of the domain, identifying information required to promote trust and shared understanding, and breaking this information into elements that need to be included within the tool. We will use our expertise in human factors to guide the design of the OCTAV tool to present these elements in an effective, integrated way to the human- autonomous system team members. Once developed, the OCTAV tool will significantly increase situation awareness and promote appropriate trust in human-autonomous system teams. Increased understanding and accurate trust will improve decision-making related to task allocation and reduced human workload, and ultimately to improved human-machine team mission performance.

* Information listed above is at the time of submission. *

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