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Original scientific paper

https://doi.org/10.21278/brod73305

MULTI-VESSELS COLLISION AVOIDANCE STRATEGY FOR AUTONOMOUS SURFACE VEHICLES BASED ON GENETIC ALGORITHM IN CONGESTED PORT ENVIRONMENT

Gongxing Wu ; College of Ocean Science and Engineering, Shanghai Maritime University, Shanghai 201306, China
Yuchao Li ; College of Ocean Science and Engineering, Shanghai Maritime University, Shanghai 201306, China
Chunmeng Jiang ; Wuhan Institute of Shipbuilding Technology, Wuhan 430050, China
Chao Wang ; College of Ocean Science and Engineering, Shanghai Maritime University, Shanghai 201306, China
Jiamin Guo ; College of Ocean Science and Engineering, Shanghai Maritime University, Shanghai 201306, China
Rui Cheng ; College of Ocean Science and Engineering, Shanghai Maritime University, Shanghai 201306, China


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Abstract

An improved genetic collision avoidance algorithm is proposed in this study to address the problem that Autonomous Surface Vehicles (ASV) need to comply with the collision avoidance rules at sea in congested sea areas. Firstly, a collision risk index model for ASV safe encounters is established taking into account the international rules for collision avoidance. The ASV collision risk index and the distance of safe encounters are taken as boundary values of the correlation membership function of the collision risk index model to calculate the optimal heading of ASV in real-time. Secondly, the genetic coding, fitness function, and basic parameters of the genetic algorithm are designed to construct the collision avoidance decision system. Finally, the simulation of collision avoidance between ASV and several obstacle vessels is performed, including the simulation of three collision avoidance states head-on situation, crossing situation, and overtaking situation. The results show that the proposed intelligent genetic algorithm considering the rules of collision avoidance at sea can effectively avoid multiple other vessels in different situations.

Keywords

collision avoidance rules; collision risk index; genetic algorithm; collision avoidance decision; autonomous surface vehicle

Hrčak ID:

281106

URI

https://hrcak.srce.hr/281106

Publication date:

1.7.2022.

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