The goal of our research is to quantitatively evaluate the mental workload of people in maritime society such as navigators, pilots, and port coordinators. Salivary NO₃^- is one of the physiological indices to quantitatively measure the mental workload and it is studied in our research. In the previous research, the experiment was conducted to measure salivary NO₃^- of port coordinators who perform radio communication in ports and harbors.^{1 Kitamura Kenichi, Quantitative Evaluation of Mental Workload for Port coordinator Using Salivary _NO3-, 2015) 2 Kitamura Kenichi, Evaluate mental workload of port coordinator based on salivary _NO3--Index, 2014)}. It is necessary to identify the events corresponding to the measurement values in the experiment so as to investigate the relationship between salivary NO₃^- and the duties corresponding to the response. Thus the duties list was constructed to classify and organize the events in the experiment, as the evet list^{3 Kamioka Daiki, Construction of port-coordinator duties list for mental workload assessment, 2017)}. In this study, the aim is to investigate the relationship between the response of salivary NO₃^- and the duties which are classified and organized in the duties list. In this research, the experiment of measuring salivary NO₃^- for port coordinators was conducted and the duties corresponding to the measurement values in the experiment were identified, the responses and the duties were analyzed. The trends were discovered by the experiment that salivary NO₃^- has a stronger response to vessel-related duties such as Communication and Watch than to duties which don’t concern vessels. Furthermore, the salivary NO₃^- of the veteran port coordinators responded to the duty of Watch, while the salivary NO₃^- of the newcomer port coordinators responded to the duty of Communication, more so than other duties.

The aim of this study is to evaluate the validity or applicability of mental workload data to simulator education. Simulator education, using ship handling simulator which can reproduce various situations, enables you to educate the beginners of seafarers effectively and it is adopted in education sites. We consider that we could educate the beginners of seafarers more effectively if we could use the mental workload data effectively in simulator education. Effective education enhances the quality of education and enables us to surely take over the skills for safe navigation to them, which is why it attributes to safe navigation. Past study evaluated the recognitions of professional by the mental workload calculated from heart rate variability. In this study, to evaluate its validity to simulator education we use the patch type device which we used in the past research and the descriptive questionnaire about own maneuvering. Subjects answer the descriptive questionnaire after their simulator exercise. After that, we show them the mental workload data calculated by patch type device during their exercise. Then they answer the descriptive questionnaire again. We evaluate the validity or applicability of mental workload data to the simulator education to observe the differences in questionnaires between before and after their referring to mental workload data.

To improve the adaptability of the Scharnov turn maneuver of large vessels, numerical simulations of the traditional and revised Scharnov turn are performed on different vessels. The maneuvering model based on the MMG standard method is adopted. The results show that the traditional maneuver is not suitable for large vessels because of their different turning abilities. According to navigation experience and simulation results, selecting a new control angle ψ₂ of around 220° with ψ₁ no change or new control angle ψ₁ of about 280° with ψ₂ no change is recommended to modify the traditional maneuver. The revised maneuvers can be effectively applied to large vessels under “man overboard” emergency situations. The simulation tests illustrate that, on average, the revised maneuver can reduce the lateral distance by 92.3%.

When marine weather data measured on board are gathered by LAN and transferred from vessels automatically, the big data sets which are connected seamlessly between the sea and the land according to a combination of the shipboard data, the ocean buoy data, AMEDAS data, etc., will have more high-resolution both temporally and spatially and will be more useful for coastal and inland seas. However, the wind data measured on board includes wake of wind caused by the structure on the vessel. Therefore, it is desirable to be corrected for each vessel. The correction of wind data measured automatically every minute on board was attempted using the reference wind data at a stationary site. The shipboard wind was measured by a vane anemometer, and the reference wind was measured by an ultrasonic anemometer. Correction for the wind direction was not necessary for the experiment ship. The corrective equation for wind speed was obtained, and is available in all wind directions. The wind speed increases by 1.3 times on board. The error observed was around 2 times of the nominal accuracy of the vane anemometer for the wind direction and was 2 or 3 times for the wind speed. The error includes the characteristics of the anemometer, the influence of the structure on the vessel, the variations of the heading direction, and the altitude adjustment for the wind speed. Our understanding of these errors that each vessel has will be advanced significantly when big data sets are gathered by the automatic measurement.