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

  • Gyeongsang National University
  • Yonsei University

Research output: Contribution to journalArticlepeer-review

65 Scopus citations

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.

Original languageEnglish
Pages (from-to)211-219
Number of pages9
JournalInternational Journal of Human-Computer Interaction
Volume37
Issue number3
DOIs
StatePublished - 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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