Intention modeling and inference for autonomous collision avoidance at sea

Rothmund, Sverre Velten; Tengesdal, Trym; Brekke, Edmund; Johansen, Tor Arne

doi:10.1016/j.oceaneng.2022.113080

Cited by 15 publications

(14 citation statements)

References 12 publications

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“…The most convenient way is assuming that the speed and course of TS are constant and the future position is estimated following the physical laws [15]. However, this assumption is unrealistic since the TS might also be aware of collision and may change their course during the OS encounter [16]. It is more crucial in confined waterways since a small error in estimating the TS trajectory could result in a collision [8].…”

Section: Contributionsmentioning

confidence: 99%

Collision avoidance of autonomous ships in inland waterways – A survey and open research problems

Tran,

Johansen,

Negenborn

2023

J. Phys.: Conf. Ser.

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Promoting autonomous surface ships in inland waterways traffic (IWT) is a potential solution towards reducing road traffic and transport emission footprints. Over the last decade, there has been a growing research on autonomous ships for open waters. However, applying this research to the IWT domain is not straightforward. The IWT, due to its confined waterways, poses a different challenge than the open sea case. Due to the confined waterways, inland ships face several hydrodynamic phenomena that they rarely encountered in the open sea, such as shallow water, banks, or ship-to-ship effects. Furthermore, the higher traffic density in inland waterways also requires a different solution for sensing and control systems. This paper offers an overview of the current developments on autonomous collision avoidance for inland waterway ships that covering different problems of safety navigation for ship in IWT. A short analysis is presented to highlight the strengths and weaknesses of each approach. We also discuss the current research gaps and what could be improved to enable the operation of inland autonomous ships.

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Section: Contributionsmentioning

confidence: 99%

Collision avoidance of autonomous ships in inland waterways – A survey and open research problems

Tran,

Johansen,

Negenborn

2023

J. Phys.: Conf. Ser.

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“…The article [8] proposes a parallelized implementation of the PSB-MPC on a Graphical Processing Unit (GPU) that reduces the computational speed of the algorithm, allowing the MPC problem to scale linearly with increasing the number of control behaviors, static and dynamic obstacles and prediction scenarios. In [9], the authors suggest a Dynamic Bayesian Network (DBN) to model and infer the intentions of other ships. Similarly, [10], proposes two-stage trajectory prediction (2-STP) algorithm to help the own ship to be aware of intention changes of target vessels and avoid collision risks.…”

Section: B Literature Reviewmentioning

confidence: 99%

Model Predictive Control for Path Following and Collision-Avoidance of Autonomous Ships in Inland Waterways

Mahipala

Johansen

2023

2023 31st Mediterranean Conference on Control and Automation (MED)

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While existing algorithms for open water navigation typically address path following and COLREGS compliant collision-avoidance, the unique challenges of inland waterways require a more tailored approach. We propose a two-level control strategy that employs Model Predictive Control (MPC) and Scenario-Based Model Predictive Control (SB-MPC) for path following and collision-avoidance. The algorithm proposes integrated strategies for handling riparian land, static obstacles, and dynamic obstacles. The method is tested in simulation.The research leading to these results has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 955.768 (MSCA-ETN AUTOBarge).

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“…Jiang et al [31] proposed a decision model based on deep reinforcement learning (DRL) and considering the attention distribution mechanism of ship pilots, in which assessment of collision risk and planning of ship movement was mainly considered. Rothmund et al [32] proposed a method using dynamic Bayesian networks to infer the intention of collision-avoidance actions of other ships in open waters, further improving the safety of results. Song et al [33] proposed an integrated classification model based on supervised learning for ship collision-avoidance course prediction, aiming to simulate the human collision-avoidance decision-making process to predict the CA steering direction of ship operators.…”

Section: Introductionmentioning

confidence: 99%

A Construction Method of a Sequential Decision Chain for Unmanned-Ship Autonomous Collision Avoidance Based on Human-Like Thinking

Wang,

Wang

et al. 2023

JMSE

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As one of the key technologies restricting the development of intelligent ships, autonomous collision avoidance has attracted the attention of many scholars all over the world. Existing research on collision-avoidance behavior focuses more on collision risk assessment and local path-planning methods for studies on the human-like sequential logic of the whole collision-avoidance process, as well as the decision-making process of various stages. Further in-depth thinking is needed urgently. Based on this, a construction method of a human-like sequential decision chain for the autonomous collision avoidance of unmanned ships is proposed through the construction of a collision-avoidance rule base and strategy set, efficient data access based on the Knowledge Graph concept, global collision risk assessment considering sequential decision process, and the construction of a complete collision-avoidance logic process to simulate the decision-making process of humans in complex multi-ship encounters in open waters. For multi-ship encounter scenarios, considering the sequential decision-making process of collision avoidance, a method was proposed to divide the collision risk of the target ship into direct collision risk and potential collision risk. The validity and reliability of the constructed sequential decision chain are verified by simulation experimental results. The results show that the method is effective for collision avoidance (especially multi-ship collision avoidance) in open waters and can provide a theoretical basis and technical support with good interpretability for the decision-making process of an unmanned ship’s autonomous collision avoidance.

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Intention modeling and inference for autonomous collision avoidance at sea

Cited by 15 publications

References 12 publications

Collision avoidance of autonomous ships in inland waterways – A survey and open research problems

Collision avoidance of autonomous ships in inland waterways – A survey and open research problems

Model Predictive Control for Path Following and Collision-Avoidance of Autonomous Ships in Inland Waterways

A Construction Method of a Sequential Decision Chain for Unmanned-Ship Autonomous Collision Avoidance Based on Human-Like Thinking

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