Publication detail

A Simple State-Space Model of Human Driver Applicable to Windy Conditions

ČELKO, J. MIHÁLIK, O. HUSÁK, M. BRADÁČ, Z.

Original Title

A Simple State-Space Model of Human Driver Applicable to Windy Conditions

Type

conference paper

Language

English

Original Abstract

The paper is concerned with the design, verification and evaluation of a car-driving test scenario for human driver assessment. The scenario implemented in Unreal Engine adds four different wind characteristics which disturb the motion of a simulated vehicle. Besides, the driver is instructed to change the driving lane at defined intervals. These forcing functions enable the identification of the human-machine loop using state-space models. The parameters characterising the human dynamics are extracted from the model of the whole loop. As opposed to rather obsolete McRuer models, this approach follows the recent trends in the modelling of human-machine systems as multiloop systems or quadratically optimal controllers. Our results suggest that the model relying on a single transfer function with 4 parameters loses prediction capabilities during more realistic scenarios, in which random disturbances, such as wind gusts, affect the vehicle. In such cases, the multiloop model with the same number of parameters is able to capture human behaviour more accurately than McRuer model.

Keywords

driving simulator, human dynamics, identification, multiloop model

Authors

ČELKO, J.; MIHÁLIK, O.; HUSÁK, M.; BRADÁČ, Z.

Released

14. 8. 2024

Publisher

Elsevier

ISBN

2405-8963

Periodical

IFAC-PapersOnLine (ELSEVIER)

Year of study

58

Number

9

State

Kingdom of the Netherlands

Pages from

229

Pages to

234

Pages count

6

URL

BibTex

@inproceedings{BUT189148,
  author="Jakub {Čelko} and Ondrej {Mihálik} and Michal {Husák} and Zdeněk {Bradáč}",
  title="A Simple State-Space Model of Human Driver Applicable to Windy Conditions",
  booktitle="18th IFAC Conference on Programmable Devices and Embedded Systems – PDeS 2024.",
  year="2024",
  journal="IFAC-PapersOnLine (ELSEVIER)",
  volume="58",
  number="9",
  pages="229--234",
  publisher="Elsevier",
  doi="10.1016/j.ifacol.2024.07.401",
  issn="2405-8963",
  url="https://www.sciencedirect.com/science/article/pii/S2405896324004907"
}