Modeling of ship trajectory in collision situations by an evolutionary algorithm

TLDR

In collision situations at sea, a decision support system should help operators choose proper manoeuvres, learn good habits, and improve intuition for future similar events. This paper presents experiments with a modified Evolutionary Planner/Navigator (EP/N), specifically the new /spl thetav/EP/N++ version, as a major component of a decision support system for collision avoidance. The modified EP/N++ treats collision avoidance as a dynamic optimization problem with static and dynamic constraints, incorporating time, variable ship speed, and moving ships to compute a safe‑optimum trajectory. The experiments produced sample ship trajectories for typical navigation scenarios, illustrating the system’s effectiveness.

Abstract

For a given circumstance (i.e., a collision situation at sea), a decision support system for navigation should help the operator to choose a proper manoeuvre, teach him good habits, and enhance his general intuition on how to behave in similar situations in the future. By taking into account certain boundaries of the maneuvering region along with information on navigation obstacles and other moving ships, the problem of avoiding collisions is reduced to a dynamic optimization task with static and dynamic constraints. This paper presents experiments with a modified version of the Evolutionary Planner/Navigator (EP/N). Its new version, /spl thetav/EP/N++, is a major component of a such decision support system. This new extension of EP/N computes a safe-optimum path of a ship in given static and dynamic environments. A safe trajectory of the ship in a collision situation is determined on the basis of this algorithm. The introduction of a time parameter, the variable speed of the ship, and time-varying constraints representing movable ships are the main features of the new system. Sample results of ship trajectories obtained for typical navigation situations are presented.