A Port Entry Risk Assessment Model Based on Bayesian Networks and Elements of the e-Navigation Concept

Abstract

Most maritime accidents are caused by human error. To reduce these errors, increase safety, protect the marine environment, reduce the administrative burden, and optimize maritime trade, the International Maritime Organization (IMO) decided to implement a concept called e-Navigation. The term e-Navigation refers to the integration of the most modern information and communication systems, both on board and ashore. The research scope of this work is the safety of navigation of the ship during the port entrance. Particularly in this case, the elements that affect the safety of the ship during port entrance are analyzed in a case study of New York port. An adaptive model based on the Bayesian Belief Network (BBN) was created, which evaluates the decision-making elements and risk assessment for port entry. The model is adaptable in the context of the different port requirements. With the presented model, all entities (ships, shipping companies, and service providers) have insight into the estimated decision to enter the port based on the given elements. Further research needs to be continued on the issue of comparing the proposed model with similar models, and how much reliance on the model burdens or facilitates the Master’s decision.