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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. | 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. | ||
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* [https://link.springer.com/content/pdf/10.1007%2F978-3-642-02809-0_45.pdf https://link.springer.com/content/pdf/10.1007%2F978-3-642-02809-0_45.pdf] | * [https://link.springer.com/content/pdf/10.1007%2F978-3-642-02809-0_45.pdf https://link.springer.com/content/pdf/10.1007%2F978-3-642-02809-0_45.pdf] | ||
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+ | * [http://link.springer.com/content/pdf/10.1007/978-3-642-02809-0_45 http://link.springer.com/content/pdf/10.1007/978-3-642-02809-0_45], | ||
+ | : [http://dx.doi.org/10.1007/978-3-642-02809-0_45 http://dx.doi.org/10.1007/978-3-642-02809-0_45] under the license http://www.springer.com/tdm | ||
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+ | * [https://link.springer.com/10.1007/978-3-642-02809-0_45 https://link.springer.com/10.1007/978-3-642-02809-0_45], | ||
+ | : [https://dblp.uni-trier.de/db/conf/hci/hci2009-11.html#MobusEGZ09 https://dblp.uni-trier.de/db/conf/hci/hci2009-11.html#MobusEGZ09], | ||
+ | : [https://dx.doi.org/10.1007/978-3-642-02809-0_45 https://dx.doi.org/10.1007/978-3-642-02809-0_45], | ||
+ | : [http://dx.doi.org/10.1007/978-3-642-02809-0_45 http://dx.doi.org/10.1007/978-3-642-02809-0_45], | ||
+ | : [https://dl.acm.org/citation.cfm?id=1601814 https://dl.acm.org/citation.cfm?id=1601814], | ||
+ | : [https://rd.springer.com/chapter/10.1007/978-3-642-02809-0_45 https://rd.springer.com/chapter/10.1007/978-3-642-02809-0_45], | ||
+ | : [https://academic.microsoft.com/#/detail/1856939722 https://academic.microsoft.com/#/detail/1856939722] |
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.
The different versions of the original document can be found in:
Published on 01/01/2009
Volume 2009, 2009
DOI: 10.1007/978-3-642-02809-0_45
Licence: CC BY-NC-SA license
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