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

Seul Chan Lee, Sol Hee Yoon, Yong Gu Ji

Research output: Contribution to journalArticlepeer-review

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
JournalInternational Journal of Human-Computer Interaction
DOIs
Publication statusAccepted/In press - 2020

Bibliographical note

Funding Information:
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (Grant-# NRF- 2019R1A6A3A12033202).

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics
  • Human-Computer Interaction
  • Computer Science Applications

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