A cooperative game approach for assessing the collision risk in multi-vessel encountering

Liu, Zihao; Wu, Zedong; Zheng, Zhongyi

doi:10.1016/j.oceaneng.2019.106175

Cited by 45 publications

(19 citation statements)

References 20 publications

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“…This justifies the problem analysis and m of safe mobile robot control using game theory methods, such as in the wo al. [19], Li and Vorobeychik [20], and Liu et al [21].…”

Section: Figurementioning

confidence: 99%

Synthesis of a Path-Planning Algorithm for Autonomous Robots Moving in a Game Environment during Collision Avoidance

Lisowski

2021

Electronics

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This paper describes and illustrates the optimization of a safe mobile robot control process in collision situations using the model of a multistep matrix game of many participants in the form of a dual linear programming problem. The synthesis of non-cooperative and cooperative game control software was performed in Matlab/Simulink software to determine the safe path of the robot when passing a greater number of other robots and obstacles. The operation of the game motion control algorithm of a mobile robot is illustrated by computer simulations made in the Matlab/Simulink program of two real previously recorded navigation situations while passing dozens of other autonomous mobile robots.

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“…This justifies the problem analysis and m of safe mobile robot control using game theory methods, such as in the wo al. [19], Li and Vorobeychik [20], and Liu et al [21].…”

Section: Figurementioning

confidence: 99%

Synthesis of a Path-Planning Algorithm for Autonomous Robots Moving in a Game Environment during Collision Avoidance

Lisowski

2021

Electronics

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“…The clustering results of DBSCAN algorithm are relatively more accurate when there is no specified number of clustering results, and DBSCAN can find clusters of any shape in the data with noisy points. The DBSCAN algorithm has been widely used in various fields presently, such as medicine, biology [38], analytical chemistry [39], marine transportation [3,4], etc. This study used the DBSCAN clustering algorithm in the process of quantifying the regional collision risk in selected water area, which improved the efficiency and visualization of the quantization process, while reducing the amount of calculation and the complexity of the calculation.…”

Section: The Regional Collision Risk Identificationmentioning

confidence: 99%

“…In general, vessel collision may cause great loss of human lives and property, as well as severe environment pollution [2]. Specifically, the collision risk is a major indicator for navigators and surveillance operators to judge the collision danger between meeting vessels [3], as well as the surveillance on shore plays an important role in preventing vessel collision accidents [4]. In practice, the operators of Vessel Traffic Service (VTS) system get access to real-time vessel data from modern navigational equipment [5], such as Automatic Radar Plotting Aids (ARPA), Automatic Identification System (AIS), Electronic Chart Display and Information System (ECDIS), etc.…”

Section: Introductionmentioning

confidence: 99%

A Novel Framework of Real-Time Regional Collision Risk Prediction Based on the RNN Approach

Liu

Wang

Cai

et al. 2020

JMSE

Self Cite

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Regional collision risk identification and prediction is important for traffic surveillance in maritime transportation. This study proposes a framework of real-time prediction for regional collision risk by combining Density-Based Spatial Clustering of Applications with Noise (DBSCAN) technique, Shapley value method and Recurrent Neural Network (RNN). Firstly, the DBSCAN technique is applied to cluster vessels in specific sea area. Then the regional collision risk is quantified by calculating the contribution of each vessel and each cluster with Shapley value method. Afterwards, the optimized RNN method is employed to predict the regional collision risk of specific seas in short time. As a result, the framework is able to determine and forecast the regional collision risk precisely. At last, a case study is carried out with actual Automatic Identification System (AIS) data, the results show that the proposed framework is an effective tool for regional collision risk identification and prediction.

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“…Borkowski [17] presented acceptable solutions for altering the course range in compliance with the International Regulations for Preventing Collisions at Sea (COLREGs Rules). Liu et al and Lisowski [18,19] proposed a different approach to preventing object collisions at sea, through use of gametheory methods to determine the safe trajectory of ships by considering elements of an indefinite nature in real navigational situations at sea. In previous works, the subjectivity of the navigator making a maneuvering decision in a collision situation has been omitted in the calculation algorithms, however this subjectivity is a factor in 88% of accidents at sea.…”

Section: Arpa Radar Remote Anti-collision Process Sensingmentioning

confidence: 99%

Multistage Dynamic Optimization with Different Forms of Neural-State Constraints to Avoid Many Object Collisions Based on Radar Remote Sensing

Lisowski

2020

Remote Sensing

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This article presents the possibility of helping navigators direct the movement of an object, while safely passing through other objects, using an artificial neural network and optimization methods. It has been shown that the best trajectory of an object in terms of optimality and security, from among many possible options, can be determined by the method of dynamic programming with the simultaneous use of an artificial neural network, by depicting the encountered objects as moving in forbidden domains. Analytical considerations are illustrated with examples of simulation studies of the developed calculation program on real navigational situations at sea. This research took into account both the number of objects encountered and the different shapes of domains assigned to the objects encountered. Finally, the optimal value of the safe object trajectory time was compared on the setpoint value of the safe passing distance of objects in given visibility conditions at sea, and the degree of discretization of calculations was determined by the density of the location of nodes along the route of objects.

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A cooperative game approach for assessing the collision risk in multi-vessel encountering

Cited by 45 publications

References 20 publications

Synthesis of a Path-Planning Algorithm for Autonomous Robots Moving in a Game Environment during Collision Avoidance

Synthesis of a Path-Planning Algorithm for Autonomous Robots Moving in a Game Environment during Collision Avoidance

A Novel Framework of Real-Time Regional Collision Risk Prediction Based on the RNN Approach

Multistage Dynamic Optimization with Different Forms of Neural-State Constraints to Avoid Many Object Collisions Based on Radar Remote Sensing

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