Towards the assessment of potential impact of unmanned vessels on maritime transportation safety

Wróbel, Krzysztof; Montewka, Jakub; Kujala, Pentti

doi:10.1016/j.ress.2017.03.029

Cited by 266 publications

(136 citation statements)

References 24 publications

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“…Combined with an enemy movement prediction model, such as the one developed by Ownby and Kott , our procedure may be of assistance in generating minimum‐risk flight journeys for UAVs. With respect to commercial applications, with the increasing focus towards the financial and safety ramifications of unmanned merchant cargo vessels , there is an opportunity to apply algorithms like ours to mitigate collision avoidance within busy ports where large ship movements will become increasingly well defined.…”

Section: Discussionmentioning

confidence: 99%

Navigating free‐floating minefields via time‐varying Voronoi graphs

Richards

Mehta

2018

Networks

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Despite their illegality, untethered free-floating naval mines are increasingly employed as part of maritime area-denial operations. By ignoring international treaties, these mines require less effort to acquire and deploy, and result in a far more dynamic-threat environment. In order to assist commanders during breach operation planning, we develop several algorithms that generate a minimum-risk journey through a field of drifting mines. Using Voronoi graphs to capture a series of static snapshots of the operational area, we present a practical methodology for building a fully connected time-varying graph (, ). Vertices  are defined as specific times and locations, and edges  define the continuous movement of a ship with simple parametric equations. The length, acceleration and risk of each edge is calculated and employed by a threat-additive A * search to quickly find a plausible, minimum-risk journey through a given minefield within a specific time frame. Using real-world data for a modern-day port and minefields of variable density, we find navigable paths that incur acceptable risk in less than 2 minutes on average. We also introduce several methods for reducing the size of (, ) and the time required for its generation.

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Section: Discussionmentioning

confidence: 99%

Navigating free‐floating minefields via time‐varying Voronoi graphs

Richards

Mehta

2018

Networks

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“…This might require going dead in water or navigating to a safer area [38], not to mention some more complicated contingencies [39]. Since the autonomous navigation mode needs to be built-in to handle such emergencies, it can also be used to a greater extent -for the whole process of navigation itself.…”

Section: Al-6mentioning

confidence: 99%

A method for uncertainty assessment and communication in safety-driven design - a case study of unmanned merchant vessel

Krzysztof¹,

Jakub²

2018

IJSS

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“…The framework of the Human Factors Analysis and Classification System (HFACS) was presented by Wiegmann et al, 2003, which was used to classify and identify contributing factors in accident factors analysis. The HFACS-framework was used to analyze maritime accidents (Chauvin et al, 2013;, potential impact of unmanned vessels on marine transportation safety (Wróbel et al, 2017), grounding accidents (Mazaheri et al, 2015), road traffic accidents (Baysari et al, 2008;Reinach et al, 2006;Patterson et al, 2010), railway accidents (Zhan et al, 2017), and classify and identify fundamental risk factors based on accident reports.…”

Section: Introductionmentioning

confidence: 99%

Use of HFACS and fault tree model for collision risk factors analysis of icebreaker assistance in ice-covered waters

et al. 2019

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With the global warming and a large amount of sea ice melting, the available Arctic Sea Route has greatly enhanced the value of Arctic shipping. Ship operations under icebreaker assistance have become an essential way to facilitate the safe navigation of merchant vessels sailing through the Arctic Sea Route in ice-covered waters, but they can also put the crew and the ship in danger caused by a possible collision between the assisted ship and the icebreaker. In this paper, a dedicated Human and Organizational Factors (HoFs) model of ship collision accidents between an assisted ship and an icebreaker is developed and analyzed with the aim to identify and classify collision risk factors. First, a modified model of the Human Factors Analysis and Classification System (HFACS) for collision accidents between a ship and an icebreaker in ice-covered waters is proposed, which helps to analyze ship collision reports. Then, a Fault Tree Analysis (FTA) model is utilized to analyze the fundamental collision risk factors according to the statistical analysis of accident reports and expert judgments based on the HFACS-SIBCI model. Finally, qualitative analysis is carried out to analyze collision risk factors under icebreaker assistance, where Risk Control Options (RCOs) are formulated. An important guidance for the risk control of ship collisions during icebreaker assistance in ice-covered waters is provided for lawmakers and shipping companies.

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Towards the assessment of potential impact of unmanned vessels on maritime transportation safety

Cited by 266 publications

References 24 publications

Navigating free‐floating minefields via time‐varying Voronoi graphs

Navigating free‐floating minefields via time‐varying Voronoi graphs

A method for uncertainty assessment and communication in safety-driven design - a case study of unmanned merchant vessel

Use of HFACS and fault tree model for collision risk factors analysis of icebreaker assistance in ice-covered waters

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