Real-time assessment and prediction on maritime risk state on the Arctic Route

Recently, the Arctic Route has become busier with the continuous melting of Arctic ice. However, navigation on the Arctic Route would be much more complex than in normal water as harsh environmental conditions, such as ice-covered water and scarce costal ports that may cause more uncertainty. Nowadays, with the rapid development of sensors on board, more related data has become available. Thus, implementing comprehensive Arctic maritime risk assessment is urgent and necessary in practice. This study proposes an Arctic maritime risk state assessment method including real-time risk state assessment and risk prediction. Specifically, real-time observation samples’ numerical risk state would be firstly obtained with projection pursuit method from 10 risk indicators. Due to the fuzzy uncertainty of single observation set, information diffusion would be applied to provide diffusion estimation on risk probability distribution in order to depict risk state precisely. Also, the accumulated distribution can be regarded as the risk prediction for next time slot and risk entropy is introduced to depict risk tendency directly. Case study based on ‘Yongsheng’ is conducted to demonstrate and verify the effectiveness of the proposed method. The findings can be useful for the operators and management on board during the Arctic voyage.