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A collaborative collision avoidance strategy for autonomous ships under mixed scenarios

Shaobo Wang, Ying–Jun Angela Zhang, Feifei Song, Wengang Mao

2023Journal of Navigation32 citationsDOI

Abstract

Abstract Ship collision avoidance has always been one of the classic topics in the field of marine research. In traditional encounter situations, officers on watch (OOWs) usually use a very high frequency (VHF) radio to coordinate each other. In recent years, with the continuous development of autonomous ships, there will be a mixed situation where ships of different levels of autonomy coexist at the same time. Under such a scenario, different decision makers have different perceptions of the current scene and different decision-making logic, so conventional collision avoidance methods may not be applicable. Therefore, this paper proposes a collaborative collision avoidance strategy for multi-ship collision avoidance under mixed scenarios. It builds a multi-ship cooperative network to determine cooperative objects and timing, at the same time. Based on a cooperative game model, a global collision avoidance responsibility distribution that satisfies group rationality and individual rationality is realised, and finally achieves a collaborative strategy according to the generalised reciprocal velocity obstacle (GRVO) algorithm. Case studies show that the strategy proposed in this paper can make all ships pass each other clearly and safely.

Topics & Concepts

Collision avoidanceCollisionRationalityComputer scienceReciprocalOperations researchSimulationComputer securityEngineeringLawPolitical sciencePhilosophyLinguisticsMaritime Navigation and SafetyMaritime Security and HistoryShip Hydrodynamics and Maneuverability
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