Modeling takeover time based on non-driving-related task attributes in highly automated driving

Sol Hee Yoon, Seul Chan Lee, Yong Gu Ji

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

This study aims to investigate the effects of non-driving-related tasks (NDRTs) on the transition of control in highly automated driving (HAD) by investigating the effects of NDRT physical, visual, and cognitive attributes during transition of control. A conceptual model of the takeover process is proposed by dividing this process into motor and mental reactions. A laboratory experiment was conducted to evaluate the effects of each NDRT attribute on the corresponding stage of the process of taking over control. A prediction model was developed using the results of multiple linear regression analysis. Additionally, a validation experiment with nine NDRTs and a baseline condition was conducted to determine the extent to which the developed model explains the takeover time for each NDRT condition. The results showed that the timing aspects of the transition of control in HAD largely consist of participant motor reactions that are affected by the physical attributes of NDRTs.

Original languageEnglish
Article number103343
JournalApplied Ergonomics
Volume92
DOIs
Publication statusPublished - 2021 Apr

Bibliographical note

Publisher Copyright:
© 2020 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics
  • Physical Therapy, Sports Therapy and Rehabilitation
  • Safety, Risk, Reliability and Quality
  • Engineering (miscellaneous)

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