Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment

TLDR

The paper proposes a model‑predictive‑control based collision avoidance system for ships. The system generates a finite set of control behaviors by varying course‑angle offsets and propulsion commands, simulates future trajectories of the ship and obstacles, evaluates COLREGS compliance and collision hazards over a prediction horizon, and selects the optimal behavior while accounting for ship dynamics, steering, propulsion, wind, current, and multiple uncertainty scenarios. Simulations demonstrate that the approach effectively handles complex scenarios with multiple dynamic obstacles and sensor or prediction uncertainty.

Abstract

This paper describes a concept for a collision avoidance system for ships, which is based on model predictive control. A finite set of alternative control behaviors are generated by varying two parameters: offsets to the guidance course angle commanded to the autopilot and changes to the propulsion command ranging from nominal speed to full reverse. Using simulated predictions of the trajectories of the obstacles and ship, compliance with the Convention on the International Regulations for Preventing Collisions at Sea and collision hazards associated with each of the alternative control behaviors are evaluated on a finite prediction horizon, and the optimal control behavior is selected. Robustness to sensing error, predicted obstacle behavior, and environmental conditions can be ensured by evaluating multiple scenarios for each control behavior. The method is conceptually and computationally simple and yet quite versatile as it can account for the dynamics of the ship, the dynamics of the steering and propulsion system, forces due to wind and ocean current, and any number of obstacles. Simulations show that the method is effective and can manage complex scenarios with multiple dynamic obstacles and uncertainty associated with sensors and predictions.