Prioritization of Influencing Factors for Remote Control Intelligent Ships Collision Based on Fuzzy Fault Tree Analysis

Navigation safety is the core of the intelligent ships development. However, the few studies focus on the qualitative and quantitative analysis of intelligent ships collision risk, and there is a lack of statistical data on bottom events related to intelligent ships. To solve this problem, this paper utilizes fuzzy theory and fault tree to assess remote control intelligent ships collision risk in inland waterways. Firstly, this paper identifies the conventional bottom events using the actual marine accident data, then identifying the influencing factors of collision risk for inland remote control intelligent ships, based on the conventional ship risk factors and in combination with the remote control intelligent ships hierarchical control structure, the impact factors of collision risk are reduced and supplemented. Constructs the fault tree of the remote control intelligent ships collision risk based on above bottom events. Secondly, using the Delphi method to evaluate the fuzziness of the failure probability of bottom events, the failure probability of the bottom events is calculated through triangular fuzzy numbers and trapezoidal fuzzy numbers. Finally, the occurrence probability of collisions involving inland remote control intelligent ships and the importance ranking of the probability of each bottom event are calculated. Through this research, the main factors affecting the collision of inland remote control intelligent ships are identified, providing an analytical basis for the development of corresponding prevention and control strategies.