A neuroergonomics approach to investigate the mental workload of drivers in real driving settings
Özet
The safety and performance of automobile drivers depend on many factors. The mental status of
the drivers is the foremost factor in ensuring driving safety, in addition to physical elements.
Studies with drivers are generally conducted in driving simulators or with scenarios close to
actual driving. This study investigated the mental workload of drivers by analyzing electroen
cephalography data recorded in totally spontaneous real driving tasks, to determine the effect of
different road conditions and driving experience. Two mental workload indexes (Frontal Theta/
Parietal Alpha and Frontal Midline Theta) and a mental fatigue index (Alpha + Theta/Beta) were
calculated using the band powers. Drivers were found to experience a higher mental workload in
road sections with heavy traffic and variable road parameters by analyzing EEG data in real
traffic. The correlation coefficients between the fatigue index and the two workload indexes were
found to be 0.577 and 0.678, respectively. The workload decreased with increasing driving
experience. Therefore, having experienced drivers perform commercial driving tasks can ensure
safer driving. By employing novel methods to handle real-world EEG data, autonomous driving
systems can also benefit.
