How we can measure the non-driving-task engagement in automated driving: Comparing flow experience and workload

Sang Min Ko, Yong Gu Ji

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

In automated driving, a driver can completely concentrate on non-driving-related tasks (NDRTs). This study investigated the flow experience of a driver who concentrated on NDRTs and tasks that induce mental workload under conditional automation. Participants performed NDRTs under different demand levels: a balanced demand–skill level (fit condition) to induce flow, low-demand level to induce boredom, and high-demand level to induce anxiety. In addition, they performed the additional N-Back task, which artificially induces mental workload. The results showed participants had the longest reaction time when they indicated the highest flow score, and had the longest gaze-on time, road-fixation time, hands-on time, and take-over time under the fit condition. Significant differences were not observed in the driver reaction times in the fit condition and the additional N-Back task, indicating that performing NDRTs that induce a high flow experience could influence driver reaction time similar to performing tasks with a high mental workload.

Original languageEnglish
Pages (from-to)237-245
Number of pages9
JournalApplied Ergonomics
Volume67
DOIs
Publication statusPublished - 2018 Feb

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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