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 language | English |
|---|---|
| Pages (from-to) | 237-245 |
| Number of pages | 9 |
| Journal | Applied Ergonomics |
| Volume | 67 |
| DOIs | |
| Publication status | Published - 2018 Feb 1 |
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All Science Journal Classification (ASJC) codes
- Human Factors and Ergonomics
- Physical Therapy, Sports Therapy and Rehabilitation
- Safety, Risk, Reliability and Quality
- Engineering (miscellaneous)
Cite this
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How we can measure the non-driving-task engagement in automated driving : Comparing flow experience and workload. / Ko, Sang Min; Ji, Yong Gu.
In: Applied Ergonomics, Vol. 67, 01.02.2018, p. 237-245.Research output: Contribution to journal › Article
TY - JOUR
T1 - How we can measure the non-driving-task engagement in automated driving
T2 - Comparing flow experience and workload
AU - Ko, Sang Min
AU - Ji, Yong Gu
PY - 2018/2/1
Y1 - 2018/2/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85032880068&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85032880068&partnerID=8YFLogxK
U2 - 10.1016/j.apergo.2017.10.009
DO - 10.1016/j.apergo.2017.10.009
M3 - Article
C2 - 29122195
AN - SCOPUS:85032880068
VL - 67
SP - 237
EP - 245
JO - Applied Ergonomics
JF - Applied Ergonomics
SN - 0003-6870
ER -