Dynamic Fuzzy Ship Domain Considering the Factors of Own Ship and Other Ships

Abstract

In this paper, we propose a novel dynamic fuzzy ship domain that considers factors associated with both one's own ship and other ships. This is in contrast to existing ship domain models that operate from the perspective of one's own ship, considering only the factors relevant to that ship. First, the domain was determined by considering the distance of the ships around one's own ship in different directions, which sufficiently accounts for factors associated with one's own ship and with the other ships. At the same time, the factors were chosen based on an analysis of their importance. Second, the domain was dynamic and modelled by establishing the relationship between the domain size and the chosen factors in different directions from one's own ship, obtained by using neural networking and wavelet decomposition. Third, the domain was developed using fuzzy sets related to different safety levels and this related the model to the practical applications of estimating spatial collision risk. The model was calibrated using Automatic Identification System (AIS) data of vessel movements in the Bohai Sea and the northern Yellow Sea. The reasonableness and the superiority of establishing a ship domain model considering the factors affecting both one's own ship and other ships were analysed, and the results show that the new model can determine the spatial collision risk of the navigational situation and is thus suitable for use as part of a ship collision avoidance system.

Research on Early Warning of Ship Danger Based on Composition Fuzzy Inference

“…However, the ship domain does not have a linear relationship with these single factors. Thus, it can be seen, the influence result of each factor on ship domain obtained by fuzzy inference is similar to other studies [22]. The comprehensive influence of various two-factor combinations on the size of the ship domain were also simulated, as shown in Figure 10.…”

“…Management factors are not considered since they are not highly relevant in opens waters. Zhou's work [22] shows that the type of ship has little effect on the size of the ship domain, and its impact is mainly reflected in the speed of the vessel. Thus, the impact of ship type will not be considered in this study to simplify the ship domain model.…”

“…Wang et al [21] proposed a fuzzy quaternion ship domain model (FQSD) and used analytic expressions to describe models. Zhou et al [22] introduced the dynamic fuzzy ship domain and established a ship domain model to determine collision risk between ships.…”

Ship Collision Risk Assessment Based on Collision Detection Algorithm

“…The proposed novel analytical framework was defined as Dynamic Quaternion Ship Domain (DQSD). D. Zhou and Z. Y. Zheng [39] proposed the dynamic fuzzy ship domain in 2019 which consider the factors associated with both own ship and others as shown in Figure 4(f). Many scholars have established many ship safety domain models on different scales to carry out a risk assessment study on the specific waters.…”

A COLREGs-Based Dynamic Navigation Safety Domain for Unmanned Surface Vehicles: A Case Study of Dolphin-I

“…When the NSD of the overtaken vehicle is being violated, the overtaking USV shall keep out of the way of the vehicle being overtaken, the overtaken USV shall keep its course and speed, as shown in Figure 1e. Since the ship domain was firstly created by Fujii and Tanaka [13], plentiful ship domains with the consideration of COLREGs have been developed, including the sector model [16], off-centering model [17], arena model [18], restricted water model [19], blocking area model [20], quaternion domain model [21,22], polygon model [23], ice area fleet navigation model [24], dynamic fuzzy model [25] and probabilistic domain model [26]. Most of these models are built by statistical methods, analytical methods and artificial intelligence methods [23].…”