A relatively small number of alternative col- lision avoidance control behaviors are formulated by con- sidering nominal and evasive maneuvers.The control behaviors are generated by varying two parameters: Offsets to the guidance course angle commanded to the autopilot, and offset the propulsions command ranging from keep speed to full reverse. Using simulated predictions of the trajectories of the obstacles and ship, the compliances with the COLREGS rules and collision hazards associated with each of the alternative control behaviors are evaluated on a finite prediction horizon into the future, and the optimal control behavior is selected. The method is conceptually and computationally simple and yet quite versatile and powerful as it can account for the dynamics of the ship, its 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 in sensors and predictions.

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

CRISTOFARO, ANDREA
2016-01-01

Abstract

A relatively small number of alternative col- lision avoidance control behaviors are formulated by con- sidering nominal and evasive maneuvers.The control behaviors are generated by varying two parameters: Offsets to the guidance course angle commanded to the autopilot, and offset the propulsions command ranging from keep speed to full reverse. Using simulated predictions of the trajectories of the obstacles and ship, the compliances with the COLREGS rules and collision hazards associated with each of the alternative control behaviors are evaluated on a finite prediction horizon into the future, and the optimal control behavior is selected. The method is conceptually and computationally simple and yet quite versatile and powerful as it can account for the dynamics of the ship, its 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 in sensors and predictions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11581/395202
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