The identification of marine traffic complexity is critical for the development and implementation of intelligent maritime transportation systems. Analyzing extensive data on ship movements enhances situational awareness and aids Vessel Traffic Services Operators (VTSOs) in the real-time monitoring of complex ship behaviors in waterways. However, the predominant systems-based analysis of marine traffic predominantly utilizes undirected Marine Traffic Situation Complex Network (MTSCN), which is inconsistent with the actual navigation situation. Firstly, a directed MTSCN is constructed in this study, which accounts for the asymmetry of navigational influences between ships. Secondly, a Node Importance Evolution Model (NIEM) is developed for the directed network of marine traffic, employing two indicators: the comprehensive degree and the comprehensive strength. Finally, the evaluation performance of the NIEM is substantiated through case studies and robustness analysis. The research results show that the construction of the directed MTSCN takes into account the differences in traffic complexity between ships, the evaluation indicators consider the transmission contributions of ship nodes within the network, and therefore fits the actual nautical situation better than the undirected MTSCN. The findings confirm that the newly developed model significantly aids VTSOs in identifying high-complexity ships requiring closer supervision, thereby enhancing marine traffic management and improving maritime safety.
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