How do visual and cognitive non-driving related tasks affect drivers’ visual attention and takeover performance in conditionally automated driving?

Hengyan Pan, William Payre, Yonggang Wang, Zhixiang Gao

Research output: Contribution to journalArticlepeer-review

Abstract

This study examines changes in visual attention during drivers’ engagement in visual or cognitive NDRTs during conditionally automated driving, and determines how these changes affect takeover performance. Seventy-five participants took part in a driving simulator study, performing three pre-takeover tasks: the three pre-takeover tasks: an auditory-imagery-verbal task (cognitive NDRT); a video-watching task (visual NDRT); and a monitoring task (baseline/non NDRT). Also, there were two hazardous events (breakdown or sudden merging of the vehicle ahead) leading to takeover requests issued with 7-s or 5-s lead times. The results revealed that NDRTs negatively affected visual attention, which caused lower saccade frequency between different areas of interest and shorter saccade amplitude. Drivers paid more visual attention to the road ahead and in-vehicle information system when performing cognitive and visual NDRTs, respectively. The visual attention of drivers performing NDRTs negatively affected takeover performance (e,g longer reaction time, heavier maximal brake pedal input, etc.). The reduction in takeover request lead time impaired takeover performance. The findings will support the design of eye tracker-based “out-of-loop” discrimination techniques and human-machine interaction interfaces in automated vehicles. This study contributes to the literature by examining how different types of NDRTs affect takeover performance, specifically focusing on drivers’ visual attention.
Original languageEnglish
Pages (from-to)(In-Press)
Number of pages27
JournalJournal of Transportation Safety and Security
Volume(In-Press)
Early online date17 Jun 2024
DOIs
Publication statusE-pub ahead of print - 17 Jun 2024

Bibliographical note

Publisher Copyright:
© 2024 Taylor & Francis Group, LLC and The University of Tennessee.

Funder

This work was supported by the Fundamental Research Funds for the Central Universities, Chang'an University (300102210657).

Keywords

  • Vehicle automation
  • visual attention
  • visual and cognitive NDRTs
  • takeover performance

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