Möbus, Claus and Eilers, Mark and Garbe, Hilke and Zilinski, Malte (2009) Probabilistic, and Empirical Grounded Modeling of Agents in Partial Cooperative (Traffic) Scenarios. In: Digital Human Modeling. Lecture Notes in Computer Science (LNCS 5620) . Springer, Berlin - Heidelberg, 423-432. ISBN 978-3-642-02808-3
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Abstract
The Human Centered Design (HCD) of Partial Autonomous Driver Assistance Systems (PADAS) requires Digital Human Models (DHMs) of human control strategies for simulations of traffic scenarios. The scenarios can be regarded as problem situations with one or more (partial) cooperative problem solvers. According to their roles models can be descriptive or normative. We present new model architectures and applications and discuss the suitability of dynamic Bayesian networks as control models of traffic agents: Bayesian Autonomous Driver (BAD) models. Descriptive BAD models can be used for simulating human agents in conventional traffic scenarios with Between-Vehicle-Cooperation (BVC) and in new scenarios with In-Vehicle-Cooperation (IVC). Normative BAD models representing error free behavior of ideal human drivers (e.g. driving instructors) may be used in these new IVC scenarios as a first Bayesian approximation or prototype of a PADAS.
Item Type: | Book Section |
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Uncontrolled Keywords: | Human Centered Design, Partial Autonomous Driver Assistance Systems, Digital Human Models, (partial) cooperative problem solvers, dynamic Bayesian networks,control models, traffic agents, Bayesian Autonomous Driver (BAD) models, Between-Vehicle-Cooperation, In-Vehicle-Cooperation |
Subjects: | Generalities, computers, information > Computer science, internet Philosophy and psychology > Psychology Technology, medicine, applied sciences > Engineering and machine engineering |
Divisions: | School of Computing Science, Business Administration, Economics and Law > Department of Computing Science |
Date Deposited: | 11 Jul 2014 08:03 |
Last Modified: | 11 Jul 2014 08:03 |
URI: | https://oops.uni-oldenburg.de/id/eprint/1844 |
URN: | urn:nbn:de:gbv:715-oops-19252 |
DOI: | 10.1007/978-3-642-02809-0_45 |
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