Collaborative Research: FMitF: Track I: Designing Safe and Robust Human-machine Interactions with Fuzzy Mental Models

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Human error is a major factor in failures across safety-critical domains. One common cause of human error is mode confusion. Mode confusion arises from a misalignment between a human operator's mental model of the system and the actual system design. Mode confusion can result in automation surprise, which can disorient the operator, increase the likelihood of operator mistakes, and erode the operator's trust in the system. This project aims to develop a new method for designing human-machine interfaces (HMIs) that minimizes this type of error. In particular, the project will develop a novel, formal foundation of mental modeling, along with techniques for rigorously evaluating the safety of HMIs and eliminating possible errors. The knowledge and tools produced in this research will be made available to researchers and designers and have potential applications to a wide range of safety-critical systems. This knowledge, in turn, will help avoid system disasters, prevent injuries, save lives, and protect critical resources across society.The central idea in this project is fuzzy mental models. These will explicitly model the vagueness inherent to how human operators understand system states and functions. This new type of mental model will be capable of capturing a wider range of human-machine interaction problems than are possible with existing mental model concepts. In support of this new mental modeling approach, this project will develop methods for (1) systematically eliciting fuzzy mental models from humans, (2) automatically analyzing an HMI to identify potential misalignments between a mental model and the system, and (3) generating suggestions for repairing misalignment flaws in HMIs and reducing the likelihood of human errors. The efficacy of these methods will be demonstrated on HMIs across a number of domains, such as automobiles, medical devices, web security, and aeronautical systems. The work will lead to improved methods for evaluating the usability of interfaces, widen the application of formal methods to new contexts, and provide resources for researchers, designers, and engineers to improve the reliability of cyber-human systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.