Möbus, Claus and Eilers, Mark and Garbe, Hilke (2011) Predicting the Focus of Attention and Deficits in Situation Awareness with a Modular Hierarchical Bayesian Driver Model. In: Digital Human Modeling. LNCS (6777). Springer, Heidelberg, Berlin, pp. 483-492. ISBN 978-3-642-21799-9
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Abstract
Situation Awareness (SA) is defined as the perception of elements in the environment within a volume of time and space, the comprehension of their meaning, and the projection of their status in the near future [1]. Lacking SA or having inadequate SA has been identified as one of the primary factors in accidents attributed to human error [2]. In this paper we present a probabilistic machine-learning-based approach for the real-time prediction of the focus of attention and deficits of SA using a Bayesian driver model as a driving monitor. This Bayesian driving monitor generates expectations conditional on the actions of the driver which are treated as evidence in the Bayesian driver model.
| Item Type: | Book Section |
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| Uncontrolled Keywords: | Focus of Attention, Situation Awareness, Bayesian Driver Model, Bayesian Driving Monitor |
| Subjects: | Generalities, computers, information > Computer science, internet Philosophy and psychology > Psychology Technology, medicine, applied sciences > Engineering and machine engineering Technology, medicine, applied sciences > Electrical engineering, electronics |
| Divisions: | School of Computing Science, Business Administration, Economics and Law > Department of Computing Science |
| Date Deposited: | 14 Feb 2014 11:40 |
| Last Modified: | 14 Feb 2014 11:40 |
| URI: | https://oops.uni-oldenburg.de/id/eprint/1782 |
| URN: | urn:nbn:de:gbv:715-oops-18636 |
| DOI: | 10.1007/978-3-642-21799-9_54 |
| Nutzungslizenz: |
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