The Impact of the Human Factor on Communication During a Collision Situation in Maritime Navigation

In this paper, the authors draw attention to the significant impact of the human factor during collision situations in maritime navigation. The problems in the communication process between navigators are so excessive that the authors propose automatic communication. This is an alternative method to the current one. The presented system comprehensively performs communication tasks during a sea voyage. To reach the mentioned goal, AI methods of natural language processing and additional properties of metaontology (ontology supplemented with objective functions) are applied. Dedicated to maritime transport applications, the model for translating a natural language into an ontology consists of multiple steps and uses AI methods of classification for the recognition of a message from the ship’s bridge. The reverse model is also multi-stage and uses a created rule-based knowledge base to create natural-language sentences built on the basis of the ontology. Validation of the model’s accuracy results was conducted through accuracy assessment coefficients for information classification, commonly used in science. Receiver operating characteristic (ROC) curves represent the results in the datasets. The presented solution of the designed architecture of the system as well as algorithms developed in the software prototype confirmed the correctness of the assumptions in the described study. The authors demonstrated that it is feasible to successfully apply metaontology and machine learning methods in the proposed prototype software for ship-to-ship communication.