After collisions at sea, situation evaluation and analysis are very important to follow-up rescue operations. At present, there are few ways give weights in the current situational safety evaluation methods after collisions of marine ships. Most safety evaluation models ignore the blurred boundaries of evaluation grades. To solve these issues, this paper identifies the safety evaluation indicator system and evaluation standards, and establishes an after-collisions safety evaluation model of maritime ships based on the extension cloud theory. This model combines the extension cloud model, the analytic hierarchy process, the entropy weight method, and game theory. Using this model, the situation safety of two collisions was evaluated. The evaluation results reflect the effectiveness of the model. In order to ensure the safety of the lives and property of marine personnel, suggestions have been made to strengthen crew training, improve ship’s self-rescue ability at sea, and establish a complete marine emergency response rescue system.

To solve the multi-ship interaction problem under the scenario of multi-modal ships, this paper designed a ship Mobile Ad hoc Network (MANET) dominated by an autonomous ship. Foremost, we discussed the development and status of autonomous ships, proposed the inevitability of multi-modal ship scenarios, and analyzed the applicability of ad hoc networks in maritime communication. After that, a ship MANET under the guidance of an autonomous ship was designed, including the system composition, network mode, and network management method. We built the ship MANET connectivity model and analyzed its attributes. In addition, the transmission capacity of the ship as a network node is also analyzed. In conclusion, we believe that the ship MANET is feasible and effective in the scenario of multi-modal ships.

Potential multi-ship conflict situations in coastal or near-shore port areas have always been one of the important factors affecting ship navigation safety and a key target of maritime traffic regulatory authorities. In recent years, with the continuous development and integration of various emerging technologies in the maritime field, maritime traffic supervision has also shown a trend of intelligent and autonomous development. The traditional supervision method dominated by human experience is evolving towards data and model-driven practices. In order to solve the problem of ship navigation safety supervision under multi-ship conflict scenarios, it is urgent to build an intelligent conflict mitigation decision-making model. Therefore, this paper designs a novel risk mitigation decision-making model for multi-ship conflict scenarios from the perspective of maritime supervision. The model proposed in this paper first extracts high-density ship clusters based on AIS (Automatic Identification System) data and uses the MCD (Mean Core Density) and PRM (Proportion of Relative Motion) as feature indicators to further mine potential multi-ship conflict scenarios. Finally, a global optimization decision-making model is constructed to effectively mitigate conflict risks. Experimental verification shows that the intelligent decision-making model for the mitigation of maritime traffic conflict proposed in this paper can autonomously identify conflict scenarios and make reasonable decisions in real time. It can effectively ensure the navigation safety of ships in multi-ship conflict scenarios and further improve the supervision level of maritime departments.