Causal Model-based Measurement and Visualization System (CMVS) for Team Performance in Command and Control of Unmanned Systems Navy SBIR FY2012.2 Sol No.: Navy SBIR FY2012.2 Topic No.: N122-137 Topic Title: Causal Model-based Measurement and Visualization System (CMVS) for Team Performance in Command and Control of Unmanned Systems Proposal No.: N122-137-0517 Firm: Perceptronics Solutions, Inc. 3527 Beverly Glen Blvd. Sherman Oaks, California 91423 Contact: Amos Freedy Phone: (818) 788-4830 Web Site: www.percsolutions.net Abstract: This proposal is to develop a "Causal Model-based Measurement and Visualization System (CMVS) for Team Performance in Command and Control of Unmanned Systems." CMVS will include methods, metrics, displays, and quantitative analysis to diagnose, visualize, and help remedy deficiencies in performance of both individual operators and teams who manage dispersed heterogeneous unmanned systems. Unmanned vehicles (UVs) are being developed and fielded at an unprecedented rate; but maximizing the benefits of autonomous or semi-autonomous robotic vehicles requires smooth integration of decisions by UV operators, consumers of the information provided by the UVs, and other command and control personnel. CMVS will identify the critical new dimensions of manned/unmanned team performance, develop metrics for capturing them in real-time scenarios and operations, integrate the metrics into a valid overall evaluation, and show how the evaluations may be used for recommendations regarding personnel, training, technology, training, and/or aiding. The key to our approach is the innovative use of an evidence-based causal decision model. The model will provide a basis for diagnosing deficiencies and recommending remedies that is grounded in cutting edge research on individual cognition, team process, and automation management. In addition, the model will provide for an integrated team performance measurement system. Benefits: Establishing the proper performance indicators for training and operations is a multidisciplinary as well as multidimensional effort. Research to date has been performed independently in six areas related to the present problem: (1) human operator team performance; (2) human-robot interaction; (3) mixed initiative systems; (4) metrics for autonomous unmanned systems; (5) warfighting simulation and evaluation, and (6) flexible decision analytic decision models for real-time diagnosis and evaluation of C3 team performance. We intend to apply and build on the existing knowledge and research findings in each area in order to synthesize a scientifically-sound performance measurement. We have already implemented a system with important measurements such as workload, trust, and situation awareness that has been empirically validated (de Visser et al., 2006). These methods and metrics have been applied to several other projects involving supervision of unmanned vehicles between teams comprising of a commander and operators (de Visser et al., 2008). The metrics have also been applied to situations of varying task load and adaptive automation (de Visser & Parasuraman, 2011). This work will provide a comprehensive basis for our proposed program. Return