Projects per year
Abstract
This study explores how drivers are affected by automation when driving in rested and fatigued conditions. Eighty-nine drivers (45 females, 44 males) aged between 20 and 85 years attended driving experiments on separate days, once in a rested and once in a fatigued condition, in a counterbalanced order. The results show an overall effect of automation to significantly reduce drivers’ workload and effort. The automation had different effects, depending on the drivers’ conditions. Differences between the manual and automated mode were larger for the perceived time pressure and effort in the fatigued condition as compared to the rested condition. Frustration was higher during manual driving when fatigued, but also higher during automated driving when rested. Subjective fatigue and the percentage of eye closure (PERCLOS) were higher in the automated mode compared to manual driving mode. PERCLOS differences between the automated and manual mode were higher in the fatigued condition than in the rested condition. There was a significant interaction effect of age and automation on drivers’ PERCLOS. These results are important for the development of driver-centered automation because they show different benefits for drivers of different ages, depending on their condition (fatigued or rested).
Original language | English |
---|---|
Article number | 30 |
Number of pages | 13 |
Journal | Safety |
Volume | 8 |
Issue number | 2 |
DOIs | |
Publication status | Published - Jun 2022 |
Keywords
- driver
- Partial automation
- Fatigue
- Age
- Gender
- Workload
- PERCLOS
- Reaction time
- gender
- workload
- partial automation
- fatigue
- reaction time
- age
ASJC Scopus subject areas
- Mechanical Engineering
- Public Health, Environmental and Occupational Health
- Safety, Risk, Reliability and Quality
- Safety Research
Fields of Expertise
- Mobility & Production
Treatment code (Nähere Zuordnung)
- Application
- Popular Scientific
Fingerprint
Dive into the research topics of 'Effects of Automation and Fatigue on Drivers from Various Age Groups'. Together they form a unique fingerprint.-
Vehicle Dynamics
Koglbauer, I. V., Lex, C., Shao, L., Semmer, M., Rogic, B., Peer, M., Hackl, A., Sternat, A. S., Schabauer, M., Samiee, S., Eichberger, A., Ager, M., Malić, D., Wohlfahrter, H., Scherndl, C. & Magosi, Z. F.
1/01/11 → …
Project: Research area
-
WACHsens - Evaluation of driver performance in semi-automated driving by physiologic, driver behavior and video based sensors
1/05/17 → 30/04/19
Project: Research project
Prizes
-
Research Data Management (RDM) Marketplace
Arefnezhad, Sadegh (Recipient) & Eichberger, Arno (Recipient), 28 Oct 2020
Prize: Prizes / Medals / Awards
File -
Respect for diversity: TU Graz diversity awards
Arefnezhad, Sadegh (Recipient), 21 Nov 2019
Prize: Prizes / Medals / Awards
File