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A collaborative collision avoidance strategy for autonomous ships under mixed scenarios

Published online by Cambridge University Press:  05 April 2023

Shaobo Wang ,
Yingjun Zhang ,
Feifei Song  and
Wengang Mao
Shaobo Wang
Affiliation:
Navigation College, Dalian Maritime University, Dalian, China Division of Marine Technology, Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Gothenburg, Sweden
Yingjun Zhang*
Affiliation:
Navigation College, Dalian Maritime University, Dalian, China
Feifei Song
Affiliation:
College of Information Science and Technology, Dalian Maritime University, Dalian, China
Wengang Mao
Affiliation:
Division of Marine Technology, Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Gothenburg, Sweden
*
*Corresponding author. E-mail: [email protected]
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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.

Keywords

autonomous shipcollaborative collision avoidancetopological networkcooperative game
Type
Research Article
Information
The Journal of Navigation , Volume 76 , Issue 2-3 , March 2023 , pp. 200 - 224
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Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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