Intent Inference-Based Ship Collision Avoidance in Encounters With Rule-Violating Vessels

Cho, Yonghoon; Kim, Jonghwi; Kim, Jinwhan

doi:10.1109/lra.2021.3130386

Cited by 7 publications

(1 citation statement)

References 23 publications

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“…In the simulation of different types of collision avoidance, the fPVO algorithm showed excellent prediction and collision avoidance abilities, and the collision avoidance paths generated by the algorithm were more practical. In another paper [23] by the same author, the fPVO algorithm was extended to R-fPVO (Reciprocal fast Probabilistic Velocity Obstacle) algorithm and applied to the collision avoidance scenario for ships that do not comply with COLREGS. The algorithm predicted the navigational intents of encountering ships by using a dynamic Bayesian network, evaluated whether the ship conforms to COLREGS, and changed the navigational trajectory accordingly.…”

Section: Recent Advancesmentioning

confidence: 99%

Research progress and prospects of intelligent planning algorithms in navigation collision avoidance

Jing

2023

Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023)

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With the development of the shipping industry, maritime transportation is preferred by more and more people, and ship collision is the first problem to be solved in intelligent navigation. Compared with collision avoidance algorithms for ground vehicles and air vehicles, there are still many problems to be solved in ship collision avoidance algorithms, among which the dynamic nature, safety, and complexity of environments will impact the development of reliable automatic collision avoidance algorithms. By analyzing the latest research on ship collision avoidance, the paper concludes that the current research mainly focuses on the rapidity, stability, and adaptability of various algorithms in complex situations, moreover, some suggestions and research directions are proposed for further research.

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Section: Recent Advancesmentioning

confidence: 99%