A simulation-based study on human factors in maritime associated with errors and failures during navigation - Tan, Ken Kok Whye (2018)
The studies of human factors in maritime are not new and have been analysed in marine accidents investigation for years. While the aviation industry had been vigorously pursuing research for human factors for decades due to the high-risk nature of flying, stakeholders in the maritime domain could not see the urgency for pursuing such research. This project aims to study human errors and failures during navigating using a full-scale maritime vessel simulator. To assist in data collection, an electroencephalogram (EEG) device, a brain-wave monitoring tool will be utilised to capture and record brain activity signals from the experiment subjects. EEG-based signals such as emotion, workload and stress are analysed and compared between four harbour pilots on different missions with different scenarios. The hypothesis in this experiment proposed that subjects will experience negative emotion, high mental workload and high stress levels when performing difficult tasks at various event points of the missions. MATLAB and Python are used to process the raw EEG signals into readable data for analysis. Following which, the stress levels will be mapped with emotion and workload levels using an algorithm. The emotion, workload and stress data will be analysed using a 4 second window 1 second step shift to obtain the 1-minute intervals for analysis along with the captured video recordings of the simulation missions. A total of 4 subjects participated in this experiment, each with a different mission and scenario lasting approximately 60 minutes. The study found that the 1-minute intervals data have some correlation to the demands of the respective simulation mission. As such, the results validated the studies of previous research as well as the potential use of EEG monitoring tool in the maritime industry. With EEG technology, its uses can be further explored into practical applications for instructors and trainers alike. This creates the possibility for all stakeholders to identify and promote suitably experienced candidates to their next career grades.