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Effects of Non-Driving-Related Task Attributes on Takeover Quality in Automated Vehicles

Authors
Lee, Seul ChanYoon, Sol HeeJi, Yong Gu
Issue Date
Mar-2021
Publisher
Lawrence Erlbaum Associates Inc.
Citation
International Journal of Human-Computer Interaction, v.37, no.3, pp 211 - 219
Pages
9
Indexed
SCIE
SSCI
SCOPUS
Journal Title
International Journal of Human-Computer Interaction
Volume
37
Number
3
Start Page
211
End Page
219
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/120606
DOI
10.1080/10447318.2020.1815361
ISSN
1044-7318
1532-7590
Abstract
This study aimed to investigate the effects of non-driving-related tasks (NDRTs) on takeover quality in the context of automated driving. Specifically, we examined the effects of three categories of NDRT attributes (i.e., physical, cognitive, and visual) on longitudinal and lateral driving measures when the drivers resumed control. We designed a driving simulator study where the participants experienced automated driving journeys and takeover situations. When the automated mode was activated, drivers engaged in one of the nine NDRTs. The results showed that the cognitive load of NDRTs had a significant negative correlation with both longitudinal and lateral control measures. However, the effects of two attributes in the physical category and one attribute in the visual category on driving performance did not show statistical significance. Overall, the findings indicated that the influence of cognitive attributes on takeover quality is more salient than that of the physical and visual attributes, which provides insights into the understanding of takeover situations to improve driving safety. © 2020 Taylor & Francis Group, LLC.
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Lee, Seulchan
ERICA 소프트웨어융합대학 (SCHOOL OF MEDIA, CULTURE, AND DESIGN TECHNOLOGY)
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