Decision-making on process risk of Arctic route for LNG carrier via dynamic Bayesian network modeling

Abstract

An increasing number of ships have chosen the suitable route to transport in Arctic waters during summer. Seeking a suitable model for risk decision-making in route planning is a necessary research topic at present. Due to its complex natural environment, there is significant uncertainty regarding ship navigation safety in Arctic waters. The process risk-based decision-making method to support route planning is established based on the dynamic Bayesian network (DBN) risk assessment model for LNG carrier collision with ice or obstacles in Arctic waters. The decision-making process for ship navigation is dynamically associated with time. Therefore, a Markov Chain (MC) is built for each dynamic node in Bayesian belief network (BBN) to realize DBN associated risk assessment, which is called process risk and is applied to decision-making. Three possible routes for ships sailing from the Vikitsky Strait to the Long Strait in Arctic waters were selected in conjunction with the objective daily change data of wind speed, temperature, wave height, and ice condition. Simulations for risk decision-making in the ship navigation process are performed. Application examples show that the ship selected either ROUTE2 (Vikitsky Strait – Laptev Sea – Sannikov Strait – Eastern Siberian Sea – Long Strait) or ROUTE3 (Vikitsky Strait – Laptev Sea – Proliv Dmitriya Lapteva – Eastern Siberian Sea – Long Strait) in August as the best navigable route.