Ship Collision Avoidance by Distributed Tabu Search

Kim, Dong-Gyun; Hirayama, Katsutoshi; Okimoto, Tenda

doi:10.12716/1001.09.01.03

Cited by 22 publications

(16 citation statements)

References 9 publications

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“…According to Section 3, the aim of course and trajectory control is to achieve obstacle avoidance and safe navigation. Therefore, in addition to the above mentioned, other intelligent optimization algorithms, such as artificial fish swarm algorithm (AFSA) [114,115], Tabu search (TS) [116], can also better achieve ship obstacle avoidance control.…”

Section: Trajectory Tracking Controlmentioning

confidence: 99%

“…Other applications of some algorithms in ship field are as follows: SA algorithm is used to determine ship routes [204]; TS algorithm is used to realize collision avoidance [116] and fleet repositioning [205]; greedy algorithm is used to arrange container transportation [206], GSA algorithm is used to arrange ship cabins [207], BFA and PSO algorithm are combined to optimize ship collision avoidance path [115], AFSA algorithm is used to realize collision avoidance [114,208].…”

Section: Number Algorithm Number Algorithmmentioning

confidence: 99%

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State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Wang

Liu

et al. 2019

JMSE

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At present, with the development of waterborne transport vehicles, research on ship faces a new round of challenges in terms of intelligence and autonomy. The concept of maritime autonomous surface ships (MASS) has been put forward by the International Maritime Organization in 2017, in which MASS become the new focus of the waterborne transportation industry. This paper elaborates on the state-of-the-art research on motion control of MASS. Firstly, the characteristics and current research status of unmanned surface vessels in MASS and conventional ships are summarized, and the system composition of MASS is analyzed. In order to better realize the self-adaptability of the MASS motion control, the theory and algorithm of ship motion control-related systems are emphatically analyzed under the condition of classifying ship motion control. Especially, the application of intelligent algorithms in the ship control field is summarized and analyzed. Finally, this paper summarizes the challenges faced by MASS in the model establishment, motion control algorithms, and real ship experiments, and proposes the composition of MASS motion control system based on variable autonomous control strategy. Future researches on the accuracy and diversity of developments and applications to MASS motion control are suggested.

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Section: Trajectory Tracking Controlmentioning

confidence: 99%

Section: Number Algorithm Number Algorithmmentioning

confidence: 99%

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Wang

Liu

et al. 2019

JMSE

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“…Its framework is given in Figure 1. (Fujii and Tanaka, 1971), (Goodwin, 1975), (Szlapczynski, 2006), (Wang et al, 2009) ship domain one-to-many centralised (Tsou and Hsueh, 2010), (Lazarowska, 2015) ant colony one-to-many centralised genetic algorithm one-to-many centralised (Lee et al, 2004) fuzzy theory one-to-many centralised (Lamb and Hunt, 1995;2000) probability one-to-many centralised (Szlapczynski, 2011; evolutionary algorithm many-to-many centralised (Hornauer, 2013), (Hornauer et al, 2015) Bayesian model many-to-many decentralised (Hu et al, 2008) negotiation one-to-one decentralised (Kim et al, 2014) local search many-to-many distributed (Kim et al, 2015) tabu search many-to-many distributed By the control procedure, a ship decides whether to proceed to the next position. If a ship does not have any target ship in the area within a certain distance from her current position and also has not yet arrived at her destination, she moves to the next position.…”

Section: I S T R I B U T E D S T O C H a S T I C S E A R C H A L G mentioning

confidence: 99%

“…To solve this problem, we applied the tabu search technique (Glover, 1989), where the ship in QLM puts her current course in a tabu list to prohibit herself from selecting that course for a certain period. The resulting algorithm was called the Distributed Tabu Search Algorithm (DTSA) (Kim et al, 2015). Figure 7 shows the procedure for DTSA.…”

Section: I S T R I B U T E D S T O C H a S T I C S E A R C H A L G mentioning

confidence: 99%

Distributed Stochastic Search Algorithm for Multi-ship Encounter Situations

2017

Self Cite

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Ship collision avoidance involves helping ships find routes that will best enable them to avoid a collision. When more than two ships encounter each other, the procedure becomes more complex since a slight change in course by one ship might affect the future decisions of the other ships. Two distributed algorithms have been developed in response to this problem: Distributed Local Search Algorithm (DLSA) and Distributed Tabu Search Algorithm (DTSA). Their common drawback is that it takes a relatively large number of messages for the ships to coordinate their actions. This could be fatal, especially in cases of emergency, where quick decisions should be made. In this paper, we introduce Distributed Stochastic Search Algorithm (DSSA), which allows each ship to change her intention in a stochastic manner immediately after receiving all of the intentions from the target ships. We also suggest a new cost function that considers both safety and efficiency in these distributed algorithms. We empirically show that DSSA requires many fewer messages for the benchmarks with four and 12 ships, and works properly for real data from the Automatic Identification System (AIS) in the Strait of Dover. K E Y W O R D S1. Ship collision avoidance.2. Distributed stochastic search algorithm. 3. Multiple ships control.

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“…It is, therefore, reasonable to investigate the methods of a ship safety handling using principles of the theory based on optimal control and differential games [5,11,12,14,16,26,27].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Methods of Determining the Safe Ship Trajectory

Lisowski¹

2016

TransNav

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Ship Collision Avoidance by Distributed Tabu Search

Cited by 22 publications

References 9 publications

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Distributed Stochastic Search Algorithm for Multi-ship Encounter Situations

Analysis of Methods of Determining the Safe Ship Trajectory

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