CAREER: Formal Tools For Analysis and Design of Collaborative Hybrid Systems

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The research objective of this Faculty Early Career Development (CAREER) Program award is to apply observability methods and reachability analysis and controller synthesis from hybrid control theory to the analysis and design of human-automation systems. Methods and tools will be created to validate and design collaborative hybrid systems. A formal framework will be developed that incorporates both qualitative human factors guidelines for user-centered design, and mathematical models of human input and user interfaces, into a mathematically rigorous framework for collaborative hybrid systems. This research specifically addresses: 1) prioritized, dynamics-driven user-interface design, 2) collaborative control synthesis, 3) verification of safety with a human in the loop, and 4) customizable displays. These techniques will be used to 1) assess information content in multi-modal user interfaces (modeled as output maps of hybrid systems), 2) identify regions in the state-space with potential for ?fighting? between the human and the automation, 3) associate state configurations with multiple levels of safety, and 4) assess efficacy of user-interfaces under imperfect information that represent inaccurate mental models or various levels of user training.If successful, the results of this research could help identify problems (such as automation surprises, fighting between the human operator and the automation, inadequate or excessive information contained in the user interface, and false or frequent alarms) in safety-critical, high-risk, or expensive collaborative systems before they are built, tested, and deployed. The proposed research and education plan will contribute to the formal methods in human computer interaction community, and to the control theory communities focused on the design of decision support aids. Developed theory, code, and data will be disseminated in a timely manner. Graduate and undergraduate students will benefit through new and resigned courses that incorporate active learning techniques, as well as through mentoring and participation in the proposed research.