Modelling dynamic maritime traffic complexity with radial distribution functions

Abstract

The identification of maritime traffic complexity is important to guide maritime surveillance operators towards the more critical areas for the real-time monitoring of the maritime traffic situation. To identify and map the traffic complexity effectively, this paper proposes a dynamic maritime traffic complexity model based on radial distribution functions. For modelling the traffic complexity, three sub complexity models are established first by addressing the speed, course and position of the ships. For each sub-model, the main variable is used for building the radial distribution function model, and a variation method is used to estimate the complexity. Finally, the overall traffic complexity can be identified and mapped by synthesizing the results from the three sub-models. The AIS data in the northern Yellow Sea of China is used for validating the proposed model. The results show that the proposed model can effectively identify the traffic complexity in the studied sea area, and have an advantage in some special sea area compared with the previous traffic complexity model. By applying the proposed model, maritime surveillance operators can better monitor the real-time traffic situation and improve their working efficiency, which are crucial for the improvement of navigational safety.