面向任务的载人深潜人机交互信息重要度评估

To identify the differences of the importance of human-machine interaction information in the cockpit of deep-sea manned submersible during complex mission,a complex network-based human-machine interaction information importance assessment method was proposed. Taking the hover sampling task as the research object,the decision ladder model and task network modeling techniques were applied to identify the human-machine interaction information elements and logical associations related to the complex task, and a complex network model of the interaction information was constructed. Based on the network topology feature parameters, the node global and local influence effect assessment indexes were proposed from the perspective of the logical influence relationship between nodes, and the integrated value of interaction information node importance was calculated by combining the interpretive structural model hierarchical weight indexes to derive the hover sampling task human-computer interaction information importance ranking.The ranking results were compared with the other four algorithms, and the submariners were invited to evaluate the subjective importance of the interaction information in the context of the actual mission process based on the proof that the calculation was valid. The results showed that the importance ranking results obtained from the study were strongly correlated with the subjective ranking results of the submariners, and the identification of important interaction information elements was consistent with the subjective perception of the submariners, which validated the effectiveness of the proposed method to identify the differences of the importance of human-machine interaction information for complex tasks.