Abstract
We propose models for the decision-making process of human drivers in an overtaking scenario. First, we mathematically formalize the overtaking problem as a decision problem with perceptual uncertainty. Then, we propose and numerically analyze risk-agnostic and risk-aware decision models, which are able to judge whether an overtaking is desirable or not. We show how a driver's decision-making time and confidence level can be primarily characterized through two model parameters, which collectively represent human risk-taking behavior. We detail an experimental testbed for evaluating the decision-making process in the overtaking scenario. Finally, we present some preliminary experimental results from two human drivers.
| Original language | English |
|---|---|
| Pages (from-to) | 15338-15345 |
| Journal | IFAC-PapersOnLine |
| Volume | 53 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2020 |
| Event | 21st IFAC World Congress 2020 - Berlin, Germany Duration: 12 Jul 2020 → 17 Jul 2020 https://www.ifac-control.org/events/ifac-world-congress-21th-wc-2020 |
Bibliographical note
Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).Research Keywords
- automated vehicles
- driving simulator
- Human decision-making
- overtaking
- risk-aware decision-making
Publisher's Copyright Statement
- This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/