Design of seafarer-centric safety system; mental workload (MWL) prediction

dc.contributor.advisor Tavacıoğlu, Leyla Özsever, Barış
dc.contributor.authorID 512152011
dc.contributor.department Deniz Ulaştırma Mühendisliği 2023-12-06T07:13:14Z 2023-12-06T07:13:14Z 2022-01-06
dc.description Thesis(Ph.D.) -- Istanbul Technical University, Graduate School, 2022
dc.description.abstract It is known that the human factor has a major effect on maritime casualties that cause great harm to the environment, economy, and maritime sector. It was stated that while human error is the primary contributor to accidents, a good part of collisions and groundings were related to the mental workload (MWL) of watchkeeping officers. Automation, mechanization, and the introduction of new technologies have changed the working conditions together with reducing the number of crew and increasing the MWL of operators. This indicates that human element-related issues will continue to be one of the major issues in marine transportation assets. In maritime-related studies, it has been analyzed mostly how the ship's environment, working period, and other factors affect the seafarers. Almost all maritime-related studies couldn't have the potential to develop an MWL prediction system for maritime operations aspect. However, lots of studies on drivers and pilots, have produced successful results for MWL prediction. Taking into consideration the fact that MWL has a major contribution to maritime casualties, the development of a real-time MWL prediction system is vitally essential for ships. By implementing the similar measurement techniques used in the studies on drivers and pilots, to maritime transportation, this study aims to classify the physiological responses of the operators that can produce an output for the state of the officer on duty as "Safe" or "Risky" from the collected physiological data and task load data during the seaborn operations. This study predicates the theories which are the statement "minimum performance requires sufficient behavioral activity" of Sheridan and Simpson (1979) together with the inverted U function of Yerkes and Dodson (1908) which presents the relationship between arousal and performance. Moreover, the theory of Young et al. (2015) which presents the relationship among mental workload, performance, task demand, and resource supply and indicates the overload region, guides this study in terms of building the structure of the experimental research. By being predicated on the above-mentioned theories, this study aimed to design a Cognitive Seafarer-Ship Interface (CSSI) which is a main part of the Seafarer-Centric Safety System. The physiological data of the 17 junior deck officers (12 subjects performed navigation scenario, 5 subjects performed cargo operation scenario) was recorded according to the design. By being correlated with the performance of the officer, the change of physiological responses of the subjects were analyzed in low and high task load levels. The medical decision-making process, which deduced "Safe" or "Risky", was run for this change. For performance measurement which is a part of a triangulated measurement strategy (Wierwille and Eggemeier, 1993), Officer Performance Model which is used for MWL classification, was developed for navigation and cargo operation tasks. Additionally, the inputs of the Task Load Estimator were defined as data transcription from navigational aids according to the results of classification. In summary, the following process was done and results were found. Ph. D.
dc.language.iso en_US
dc.publisher Graduate School
dc.sdg.type Goal 3: Good Health and Well-being
dc.subject maritime safety
dc.subject deniz güvenliği
dc.subject electrophysiological data acquisition
dc.subject elektrofizyolojik bilgi toplama
dc.subject seafarers
dc.subject gemi adamları
dc.subject mental workload
dc.subject mental iş yükü
dc.title Design of seafarer-centric safety system; mental workload (MWL) prediction
dc.title.alternative Gemi insanı-merkezli emniyet sisteminin tasarımı; mental iş yükü öngörüsü
dc.type doctoralThesis
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