Name
Abstract | ||
|---|---|---|
This study proposes a probabilistic decision-making model for driving decisions. The decision-making process that is modeled stochastically is part of the Human Driver Model developed in an earlier study, in which perception, world-model and reflexive behavior are represented as separate modules. Finite-state machine design guidelines for decision-making models are provided to maximize state observability and resolution while maintaining a manageable size for state-machine. Two decision-making models useful for estimation and prediction of driver behavior are presented and one scenario-safety estimation application that uses the proposed decision-making model is given to illustrate the proposed methodology. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ITSC.2011.6082911 | ITSC |
Keywords | Field | DocType |
decision making,finite state machines,probability,road safety,transportation,decision-making models,decision-making process,driving decisions,finite-state machine design guidelines,human driver model,probabilistic decision-making model,probabilistic model,reflexive behavior,scenario-safety estimation application,state observability,mathematical models,behavior | Observability,Simulation,Finite-state machine,Machine design,Statistical model,Engineering,Probabilistic logic,Mathematical model,Perception | Conference |
ISSN | ISBN | Citations |
2153-0009 | 978-1-4577-2198-4 | 5 |
PageRank | References | Authors |
0.51 | 2 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arda Kurt | 1 | 18 | 1.65 |
| Ümit Özgüner | 2 | 1014 | 166.59 |