The Mental Workload And Alertness Levels Of Train Drivers Under Simulated Conditions Based On Electroencephalogram Signals

ABSTRACT

It was suggested by most researchers that train drivers’ workload and alertness levels attribute to train accidents. The main objective of this study is to determine the significant patterns of mental workload and alertness levels of train drivers with respect to the conditions. The data are collected from simulation experiments on 15 professional train drivers. The simulation experiments are performed under three driving conditions (i.e. daytime, rainy daytime and rainy night) using a train driving simulator set. Electroencephalogram (EEG) signals are collected from six significant points on the body of the subjects. It is found that the mental workload of the train drivers tends to be high during rainy night driving condition and sleepiness occurs which is indicative of low vigilance. The beta amplitude increases under rainy night driving condition which may be attributed to viewing difficulties while driving in the dark. The results reveal that there is a significant different between each session (p = 0.042) especially with the pattern for rainy night driving. It is also observed that there is lower mental workload among the train drivers, which indicates that the train drivers are detached from their work.