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The Stability of Human Supervisory Control Operator Behavioral Models Using Hidden Markov Models

Publication ,  Conference
Zhu, H; Cummings, ML
Published in: IEEE International Conference on Intelligent Robots and Systems
November 1, 2019

Human supervisory control (HSC) is a widely used knowledge-based control scheme, in which human operators are in charge of planning and making high-level decisions for systems with embedded autonomy. With the variability of operators' behaviors in such systems, the stability of an operator modeling technique, i.e., that a modeling approach produces similar results across repeated applications, is critical to the extensibility and utility of such a model. Using an unmanned vehicle simulation testbed where such vehicles can be hacked, we compared two operator behavioral models from two different experiments using a hidden Markov modeling (HMM) approach. The resulting HMM models revealed operators' dominant strategies when conducting hacking detection tasks. The similarity between these two models was measured via multiple aspects, including model structure, state distribution, divergence distance, and co-emission probability distance. The similarity measure results demonstrate the stability of modeling human operators in HSC scenarios using HMM models. These results indicate that even when operators perform differently on specific tasks, such an approach can reliably detect whether strategies change across different experiments.

Duke Scholars

Published In

IEEE International Conference on Intelligent Robots and Systems

DOI

EISSN

2153-0866

ISSN

2153-0858

ISBN

9781728140049

Publication Date

November 1, 2019

Start / End Page

6971 / 6978
 

Citation

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Zhu, H., & Cummings, M. L. (2019). The Stability of Human Supervisory Control Operator Behavioral Models Using Hidden Markov Models. In IEEE International Conference on Intelligent Robots and Systems (pp. 6971–6978). https://doi.org/10.1109/IROS40897.2019.8968537
Zhu, H., and M. L. Cummings. “The Stability of Human Supervisory Control Operator Behavioral Models Using Hidden Markov Models.” In IEEE International Conference on Intelligent Robots and Systems, 6971–78, 2019. https://doi.org/10.1109/IROS40897.2019.8968537.
Zhu H, Cummings ML. The Stability of Human Supervisory Control Operator Behavioral Models Using Hidden Markov Models. In: IEEE International Conference on Intelligent Robots and Systems. 2019. p. 6971–8.
Zhu, H., and M. L. Cummings. “The Stability of Human Supervisory Control Operator Behavioral Models Using Hidden Markov Models.” IEEE International Conference on Intelligent Robots and Systems, 2019, pp. 6971–78. Scopus, doi:10.1109/IROS40897.2019.8968537.
Zhu H, Cummings ML. The Stability of Human Supervisory Control Operator Behavioral Models Using Hidden Markov Models. IEEE International Conference on Intelligent Robots and Systems. 2019. p. 6971–6978.

Published In

IEEE International Conference on Intelligent Robots and Systems

DOI

EISSN

2153-0866

ISSN

2153-0858

ISBN

9781728140049

Publication Date

November 1, 2019

Start / End Page

6971 / 6978