Exploring the Driver’s Mental Control Model : Concepts and Insights
Hong, Sara LU
and Yang, Ji Hyun
(2024)
25th International Conference on Human-Computer Interaction, HCII 2023
In Communications in Computer and Information Science
1958 CCIS.
p.431-437
- Abstract
This study aims to develop a comprehensive model that accurately represents the perceptual system of drivers and provides insights into their behavior. Existing models, namely the Skill-Rule-Knowledge model and the dynamic driving task model, were integrated. This integrated model successfully elucidates the sequential processes involved in sensation reception, recognition, judgment, and control. Furthermore, the study investigates the drivers’ behavior during takeover situations. Specifically, the model’s sequence was determined by considering two distinct scenarios: unplanned operational design domain (ODD) exit resulting from automated driving system (ADS) failure and planned ODD exit during highway driving. Empirical data was... (More)
This study aims to develop a comprehensive model that accurately represents the perceptual system of drivers and provides insights into their behavior. Existing models, namely the Skill-Rule-Knowledge model and the dynamic driving task model, were integrated. This integrated model successfully elucidates the sequential processes involved in sensation reception, recognition, judgment, and control. Furthermore, the study investigates the drivers’ behavior during takeover situations. Specifically, the model’s sequence was determined by considering two distinct scenarios: unplanned operational design domain (ODD) exit resulting from automated driving system (ADS) failure and planned ODD exit during highway driving. Empirical data was gathered using a simulator with 36 participants in the ADS failure situation and 40 participants in the highway exit situation. Two takeover situations were compared based on drivers’ perception time and perception-reaction time. The results revealed that both the perception time and perception-reaction time were significantly longer in the highway exit situation compared to the ADS failure situation. These findings have important implications for understanding the differences in drivers’ cognitive processes and reaction times in varying driving contexts. It is worth noting that this model will undergo further refinement, validation, and application to other features of ADS or different driving scenarios in future research.
(Less)
- author
- Hong, Sara
LU
and Yang, Ji Hyun
- publishing date
- 2024
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Driver Behavior, Driver Model, Takeover
- host publication
- HCI International 2023 – Late Breaking Posters - 25th International Conference on Human-Computer Interaction, HCII 2023, Proceedings
- series title
- Communications in Computer and Information Science
- editor
- Stephanidis, Constantine ; Antona, Margherita ; Ntoa, Stavroula and Salvendy, Gavriel
- volume
- 1958 CCIS
- pages
- 7 pages
- publisher
- Springer Science and Business Media B.V.
- conference name
- 25th International Conference on Human-Computer Interaction, HCII 2023
- conference location
- Copenhagen, Denmark
- conference dates
- 2023-07-23 - 2023-07-28
- external identifiers
-
- scopus:85180536759
- ISSN
- 1865-0929
- 1865-0937
- ISBN
- 9783031492143
- DOI
- 10.1007/978-3-031-49215-0_51
- language
- English
- LU publication?
- no
- additional info
- This publication was produced during my PhD at Kookmin University, prior to my employment at LU. Included here for profile completeness.
- id
- 906c5201-174f-4ea9-a786-dcf25bc137e0
- date added to LUP
- 2025-07-08 14:18:40
- date last changed
- 2025-08-13 03:40:02
@inproceedings{906c5201-174f-4ea9-a786-dcf25bc137e0,
abstract = {{<p>This study aims to develop a comprehensive model that accurately represents the perceptual system of drivers and provides insights into their behavior. Existing models, namely the Skill-Rule-Knowledge model and the dynamic driving task model, were integrated. This integrated model successfully elucidates the sequential processes involved in sensation reception, recognition, judgment, and control. Furthermore, the study investigates the drivers’ behavior during takeover situations. Specifically, the model’s sequence was determined by considering two distinct scenarios: unplanned operational design domain (ODD) exit resulting from automated driving system (ADS) failure and planned ODD exit during highway driving. Empirical data was gathered using a simulator with 36 participants in the ADS failure situation and 40 participants in the highway exit situation. Two takeover situations were compared based on drivers’ perception time and perception-reaction time. The results revealed that both the perception time and perception-reaction time were significantly longer in the highway exit situation compared to the ADS failure situation. These findings have important implications for understanding the differences in drivers’ cognitive processes and reaction times in varying driving contexts. It is worth noting that this model will undergo further refinement, validation, and application to other features of ADS or different driving scenarios in future research.</p>}},
author = {{Hong, Sara and Yang, Ji Hyun}},
booktitle = {{HCI International 2023 – Late Breaking Posters - 25th International Conference on Human-Computer Interaction, HCII 2023, Proceedings}},
editor = {{Stephanidis, Constantine and Antona, Margherita and Ntoa, Stavroula and Salvendy, Gavriel}},
isbn = {{9783031492143}},
issn = {{1865-0929}},
keywords = {{Driver Behavior; Driver Model; Takeover}},
language = {{eng}},
pages = {{431--437}},
publisher = {{Springer Science and Business Media B.V.}},
series = {{Communications in Computer and Information Science}},
title = {{Exploring the Driver’s Mental Control Model : Concepts and Insights}},
url = {{http://dx.doi.org/10.1007/978-3-031-49215-0_51}},
doi = {{10.1007/978-3-031-49215-0_51}},
volume = {{1958 CCIS}},
year = {{2024}},
}