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Publication detail
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
https://www.sciencedirect.com/science/article/pii/S2405896324004907
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" }