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[FWHT15] L. Feng, C. Wiltsche, L. Humphrey, U. Topcu. Controller Synthesis for Autonomous Systems Interacting with Human Operators. In International Conference on Cyber-Physical Systems, pages 70-79, ACM. 2015. [pdf] [bib]
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Notes: Notes: The PRISM and PRISM-games models for this paper are available at http://www.prismmodelchecker.org/casestudies/human-uav.php
Abstract. We propose an approach to synthesize control protocols for autonomous systems that account for uncertainties and imperfections in interactions with human operators. As an illustrative example, we consider a scenario involving road network surveillance by an unmanned aerial vehicle (UAV) that is controlled remotely by a human operator but also has a certain degree of autonomy. Depending on the type (i.e., probabilistic and/or nondeterministic) of knowledge about the uncertainties and imperfections in the operator- autonomy interactions, we use abstractions based on Markov decision processes and augment these models to stochastic two-player games. Our approach enables the synthesis of operator-dependent optimal mission plans for the UAV, highlighting the effects of operator characteristics (e.g., workload, proficiency, and fatigue) on UAV mission performance; it can also provide informative feedback (e.g., Pareto curves showing the trade-offs between multiple mission objectives), potentially assisting the operator in decision-making.