Ship domain applied to determining distances for collision avoidance manoeuvres in give-way situations

Szlapczynski, Rafal; Krata, P.; Szlapczynska, Joanna

doi:10.1016/j.oceaneng.2018.07.041

Cited by 81 publications

(36 citation statements)

References 31 publications

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“…Such solutions (e.g. [19]- [22]), however needs to be adapted and investigated for situations with MASS involved as well.…”

Section: Discussion Of Selected Results and Some Preliminary Conclusionmentioning

confidence: 99%

Merging Conventionally Navigating Ships and MASS - Merging VTS, FOC and SCC?

Baldauf¹,

Fischer²,

Kitada³

et al. 2019

TransNav

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“…Such solutions (e.g. [19]- [22]), however needs to be adapted and investigated for situations with MASS involved as well.…”

Section: Discussion Of Selected Results and Some Preliminary Conclusionmentioning

confidence: 99%

Merging Conventionally Navigating Ships and MASS - Merging VTS, FOC and SCC?

Baldauf¹,

Fischer²,

Kitada³

et al. 2019

TransNav

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“…Algorithms for path planning employ various models for the ship domains considered in anti-collision (often called obstacle avoidance) algorithms. In Reference [14,15], a numerically derived ship domain calculated on the basis of movement vectors is proposed. In Reference [16], a moving obstacle is modeled as an elliptical domain, according to the recommendations of the International Maritime Organization (IMO), and a complex system based on path planning with a constrained A* approach in a confined maritime environment is presented.…”

Section: Related Workmentioning

confidence: 99%

Shore Construction Detection by Automotive Radar for the Needs of Autonomous Surface Vehicle Navigation

Stateczny

Kazimierski

Burdziakowski

et al. 2019

IJGI

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Autonomous surface vehicles (ASVs) are becoming more and more popular for performing hydrographic and navigational tasks. One of the key aspects of autonomous navigation is the need to avoid collisions with other objects, including shore structures. During a mission, an ASV should be able to automatically detect obstacles and perform suitable maneuvers. This situation also arises in near-coastal areas, where shore structures like berths or moored vessels can be encountered. On the other hand, detection of coastal structures may also be helpful for berthing operations. An ASV can be launched and moored automatically only if it can detect obstacles in its vicinity. One commonly used method for target detection by ASVs involves the use of laser rangefinders. The main disadvantage of this approach is that such systems perform poorly in conditions with bad visibility, such as in fog or heavy rain. Therefore, alternative methods need to be sought. An innovative approach to this task is presented in this paper, which describes the use of automotive three-dimensional radar on a floating platform. The goal of the study was to assess target detection possibilities based on a comparison with photogrammetric images obtained by an unmanned aerial vehicle (UAV). The scenarios considered focused on analyzing the possibility of detecting shore structures like berths, wooden jetties, and small houses, as well as natural objects like trees or other kinds of vegetation. The recording from the radar was integrated into a single complex radar image of shore targets. It was then compared with an orthophotomap prepared from AUV camera pictures, as well as with a map based on traditional land surveys. The possibility and accuracy of detection for various types of shore structure were statistically assessed. The results show good potential for the proposed approach—in general, objects can be detected using the radar—although there is a need for development of further signal processing algorithms.

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“…Based on this fundamental concept various models and application have been proposed, e.g. (Szlapczynski et al, 2018;Wang, 2010), etc. In this paper, we replace the circular C onfP with a static elliptical ship domain as the new criteria for collision candidate.…”

Section: Elliptical Ship Domainmentioning

confidence: 99%

“…The parameters of such area are semimajor and semi-minor axis, respectively. In this paper, they are set as 8 times and 4 times of own ship's length based on the research by (Szlapczynski et al, 2018). To integrate such domain into the TD-NLVO, a mathematical function needs to be proposed.…”

Section: Elliptical Ship Domainmentioning

confidence: 99%

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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Ship domain applied to determining distances for collision avoidance manoeuvres in give-way situations

Cited by 81 publications

References 31 publications

Merging Conventionally Navigating Ships and MASS - Merging VTS, FOC and SCC?

Merging Conventionally Navigating Ships and MASS - Merging VTS, FOC and SCC?

Shore Construction Detection by Automotive Radar for the Needs of Autonomous Surface Vehicle Navigation

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

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