A solving algorithm of navigational collision risk through data analysis of fishing vessel activities

Abstract

There is increasing concern that many collision accidents happened in fishing areas. The probability of collision risk increases due to the vulnerability of fishing areas where the collision accidents involving large ships may cause serious consequence. To improve collision risk assessment, this paper focuses on solving navigational collision risk based on the analysis of fishing vessel activities using Automatic Identification System (AIS) data. AIS provides a high level of solution to assess fishing activities to reduce the collision influence of fishing vessels. The identification of fishing activities should be handled among the large number of fishing vessels. Fuzzy C-Means clustering method is applied to accomplish the clusters considering the position and speed of fishing vessels. The distance to the cluster of fishing area and its size are chosen as main factors to infer the vulnerability of fishing area using fuzzy logic reasoning. Distance to the Closest Point of Approach (DCPA) and Time to the Closest Point of Approach (TCPA) are used as significant variables to calculate basic collision risk in practice. Then basic collision risk and vulnerability of fishing boats are combined to build an algorithm to solve navigational collision risk for e-Navigation. Simulation is implemented to validate its effectiveness.