Ship collision candidate detection method: A velocity obstacle approach

Chen, Pengfei; Huang, Yamin; Mou, Junmin; Gelder, Pieter van

doi:10.1016/j.oceaneng.2018.10.023

Cited by 118 publications

(45 citation statements)

References 30 publications

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“…According to the definition in (Chen et al, 2018), collision candidate is the pair of ships in an encounter process where their spatiotemporal relationships satisfy certain criteria that has the potential for collision. This definition provides an open framework that can integrate the selected criteria of geometric collision probability into account.…”

Section: Methodsmentioning

confidence: 99%

“…During the encounter process, the kinematic information of both ships can be updated, hence their influence on the velocity obstacle induced by the target. Therefore, in (Chen et al, 2018) and this work the non-linear velocity obstacle algorithm was applied as the fundamental tool for collision candidate detection. The basic theory of Non-linear velocity obstacle algorithm is shown in Fig.…”

Section: Td-nlvo Algorithmmentioning

confidence: 99%

“…The basic theory of Non-linear velocity obstacle algorithm is shown in Fig. 1: Figure 1 Basic illustration of Non-linear Velocity Obstacle algorithm (Chen et al, 2018) Suppose that ship A and B in Fig. 1 are in an encounter situation.…”

Section: Td-nlvo Algorithmmentioning

confidence: 99%

“…To obtain geometric P , generally, there are two major categories of approaches: 1) indicator-based approach and 2) safety boundary approach (Chen et al, 2018). The indicator-based approach determines the encounter situation of ships based on certain indicators that can reflect their spatiotemporal proximity, e.g.…”

Section: Introductionmentioning

confidence: 99%

“…The reason caused such issues is that traditional methods do not consider encounter as a process, instead of the instant information of encounter, either using indicator or safety boundary, are introduced to determine the situation. In (Chen et al, 2018) the authors have changed this perspective, to consider the encounter as a process and determine collision candidate using Time Discrete Non-line Velocity obstacle algorithm (TD-NLVO). The results of this paper indicate that compared with traditional methods, the new results of this new algorithm show high reliability.…”

Section: Introductionmentioning

confidence: 99%

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Integration of Elliptical Ship Domains and Velocity Obstacles for Ship Collision Candidate Detection

Chen¹,

Gelder²,

Mou³

2019

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The maritime shipping industry has been making significant contributions to the development of the regional and global economy. However, maritime accidents and their severe consequences have been posing an incrementing risk to the individuals and societies. It is therefore important to conduct risk analysis on such accidents to support maritime safety management. In this paper, a modified ship collision candidate detection method is proposed as a tool for collision risk analysis in ports and waterways. Time-Discrete Velocity Obstacle algorithm (TD-NLVO) is utilized to detect collision candidates based on the encounter process extracted from AIS data. Ship domain model was further integrated into the algorithm as the criteria for determination. A case study is conducted to illustrate the efficacy of the improved model, and a comparison between the existing method and actual ship trajectories are also performed. The results indicate that with the integration of ship domain, the new method can effectively detect the encounters with significant collision avoidance behaviours. The choice of criteria can have a significant influence on the results of collision candidate detection.

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Section: Methodsmentioning

confidence: 99%

Section: Td-nlvo Algorithmmentioning

confidence: 99%

Section: Td-nlvo Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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