Möbus, Claus and Eilers, Mark (2011) Integrating Anticipatory Competence into a Bayesian Driver Model. In: Human Modelling in Assisted Transportation: Models, Tools and Risk Methods. Springer, Heidelberg, Berlin, pp. 225-232. ISBN 978-8847018204

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Official URL: http://link.springer.com/chapter/10.1007%2F978-88-...


We present a probabilistic model architecture combining a layered model of human driver expertise with a cognitive map and beliefs about the driver-vehicle state to describe the effect of anticipations on driver actions. It implements the sensory-motor system of human drivers with autonomous, goal-based attention allocation and anticipation processes. The model has emergent properties and combines reactive with prospective behavior based on anticipated or imagined percepts obtained from a Bayesian cognitive map. It has the ability to predict agent’s behavior, to abduct hazardous situations (what could have been the initial situation), to generate anticipatory plans, and control countermeasures preventing hazardous situations.

Item Type: Book Section
Uncontrolled Keywords: Probabilistic Model Architecture, Human Driver Expertise, Attention Allocation, Prospective Behavior, Bayesian Cognitive map, Abduction of Hazardous Situations, Anticipatory Plans, Control Countermeasures, Prevention of Hazardous Situations
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: 21 Feb 2014 09:54
Last Modified: 21 Feb 2014 09:54
URI: https://oops.uni-oldenburg.de/id/eprint/1805
URN: urn:nbn:de:gbv:715-oops-18863
DOI: 10.1007/978-88-470-1821-1_24

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