An intelligent method for real-time ship collision risk assessment and visualization

Abstract

Collision risk assessment in real-time is of critical importance to prevent ship collision at sea. Therefore, this paper presents a real-time collision risk assessment method based on an improved Non-linear Velocity Obstacle (NL-VO) algorithm. The proposed method consists of two main modules: trajectory uncertainty module assumes that the increase in the radius of the circular restricted area is consistent with the Wiener process; collision risk assessment module utilizes the NL-VO algorithm combined with the dynamic circular restricted area to evaluate the potential collisions. Several encounter scenarios in a specific port channel are designed to demonstrate the feasibility of using this proposed method to assess ship collision risk in real-time. The results are visualized and illustrated that this improved NL-VO algorithm can timely identify a ship that is in danger of colliding with the own ship and know when the collision will occur, which contributes to reducing ship collision occurrence probability.