A Simulator-Based Tidal Current Response Competence Evaluation Framework for Remote Operators

A remote operator (RO) of Maritime Autonomous Surface Ships (MASSs) is required to respond to the effects of external forces, such as tidal currents, and ensure safe, efficient, and sustainable navigation. However, previous studies primarily focus on the physical movement changes of the ship caused by tidal currents, with limited research addressing the impact of external forces on ship maneuverability and steering response. Therefore, analysis of an RO’s steering competence and identification features for training is important. In the context of sustainable maritime operations and navigation, the purpose of this study is to analyze the competence of ROs in steering ships under the effects of tidal currents and to identify priority training features as a foundational framework for future applications to MASS remote operation training. Twenty third-year cadets at Mokpo National Maritime University participated in simulator experiments designed to analyze steering competence in the presence and absence of tidal currents in a controlled environment. The experimental results showed the difference in steering performance considering the effect of tidal currents, and machine learning algorithms were used to identify priority training features. Machine learning analysis ranked Altering to ROT zero time (ART) and Maximum port ROT (MRT) as the two most influential steering features among the four identified variables, consistently showing the highest importance scores across all models. This simulator-based study identifies tidal current response steering features as a foundational framework for RO training and competence evaluation, which may inform the design of future MASS remote operation training programs after further validation.