Name
Title | ||
|---|---|---|
Probabilistic and Empirical Grounded Modeling of Agents in (Partial) Cooperative Traffic Scenarios |
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.
|
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-02809-0_45 | HCI (11) |
Keywords | Field | DocType |
new ivc scenario,mixture- of-experts model,visual attention allocation,probabilistic detection of anomalies,human control strategy,digital human response models,learning of human control strategies,bayesian approximation,partial cooperative problem solvers,probabilistic driver models,shared space,graphical modeling,dynamic bayesian network,normative bad model,descriptive bad model,human agent,bayesian autonomous driver,human behavior learning and transfer,distributed cognition,dynamic bayesian net,driver assistance systems,traffic agents,cooperative traffic scenarios,ideal human driver,bayes- ian autonomous driver models,partial autonomous assistance system,conventional traffic scenario,bayesian assistance system,psychology,graphical model,human behavior,human centered design,role models | Shared space,Normative,Advanced driver assistance systems,Artificial intelligence,Probabilistic logic,Engineering,Hidden Markov model,Machine learning,User-centered design,Dynamic Bayesian network,Bayesian probability | Conference |
Volume | ISSN | Citations |
5620 | 0302-9743 | 5 |
PageRank | References | Authors |
0.86 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Claus Möbus | 1 | 58 | 15.18 |
| Mark Eilers | 2 | 20 | 3.70 |
| Hilke Garbe | 3 | 21 | 4.69 |
| Malte Zilinski | 4 | 5 | 1.20 |