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Driver fatigue may impose the risk of crashes and is a leading cause of death in transportation industry. This study aimed to detect driver cognitive fatigue based on changes in EEG frequency bands in non-professional drivers during a simulated driving task. In a descriptive-analytical study, 12 healthy male car drivers took part in a two hour driving session on a simulated monotonous road, while EEG signals were recoded. The four EEG frequency bands, including delta, theta, alpha and beta were extracted and calculated using Fast Fourier Transform technique. The findings suggest significant differences in delta, theta, alpha and beta activities at the prefrontal, parietal sites, and also in the average activity during the driving sections. There were significant differences at the central site for delta, theta and alpha activities. At the temporal site, significant differences were found for delta and beta activities. No significant differences were observed for the four frequency bands at the occipital site. To prevent the risk of cognitive fatigue in transportation industry, it is necessary to estimate the changes in EEG activities during driving. The findings proposed the drop in beta activity as a potential fatigue indicator, but for developing a fatigue countermeasure device, some implications still exist that need further investigation.

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Driver fatigue is one of the main causes of road accidents. This study aimed to estimate bus driver fatigue through performance measures in a virtual driving environment. The study was conducted on thirty professional male bus drivers participated in a two-hour drive session. The driver subjective fatigue was assessed by Fatigue Visual Analogue Scale (F-VAS) on 10 min intervals. At the same time, the performance measures of lane drifting as mean and standard deviation of bus lateral position (SDLP) were calculated during the simulated driving task. The findings presented a rising trend in subjective fatigue level with increasing the time-on-task of driving. Time-on-task of driving was the most effective factor on fatigue self-evaluation. The drivers showed a significant correlation between F-VAS score and SDLP. The findings revealed a strong correspondence between SDLP and driver subjective fatigue based on group mean data, but individual differences may affect the driving performance which should not be ignored in future investigation.