A quantitative approach for delineating principal fairways of ship passages through a strait

Chen, Jinhai; Lu, Feng; Peng, Guojun

doi:10.1016/j.oceaneng.2015.04.077

Cited by 44 publications

(19 citation statements)

References 49 publications

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“…The work of [7] shows that the combination of automated grouping of AIS data opens up a range of possibilities for analysis of ship traffic and maneuvering from simple statistical studies of current traffic to the inference of a prototypical voyage plan for a group of ships. In [8], the authors presented a space-use method, which is available and popular in the domain of movement ecology, in an attempt to analyze Principal Fairways (PF). The used AIS data together to bathymetric data in order to identify when and where strait corridors are used by transit-passage vessels.…”

Section: Related Workmentioning

confidence: 99%

Data Analysis, Simulation and Visualization for Environmentally Safe Maritime Data

Μaragoudakis

2019

Algorithms

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Marine transportation in Aegean Sea, a part of the Mediterranean Sea that serves as gateway between three continents has recently seen a significant increase. Despite the commercial benefits to the region, there are certain issues related to the preservation of the local ecosystem and safety. This danger is further deteriorated by the absence of regulations on allowed waterways. Marine accidents could cause a major ecological disaster in the area and pose big socio-economic impacts in Greece. Monitoring marine traffic data is of major importance and one of the primary goals of the current research. Real-time monitoring and alerting can be extremely useful to local authorities, companies, NGO’s and the public in general. Apart from real-time applications, the knowledge discovery from historical data is also significant. Towards this direction, a data analysis and simulation framework for maritime data has been designed and developed. The framework analyzes historical data about ships and area conditions, of varying time and space granularity, measures critical parameters that could influence the levels of hazard in certain regions and clusters such data according to their similarity. Upon this unsupervised step, the degree of hazard is estimated and along with other important parameters is fed into a special type of Bayesian network, in order to infer on future situations, thus, simulating future data based on past conditions. Another innovative aspect of this work is the modeling of shipping traffic as a social network, whose analysis could provide useful and informative visualizations. The use of such a system is particularly beneficial for multiple stakeholders, such as the port authorities, the ministry of Mercantile Marine, etc. mainly due to the fact that specific policy options can be evaluated and re-designed based on feedback from our framework.

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Section: Related Workmentioning

confidence: 99%

Data Analysis, Simulation and Visualization for Environmentally Safe Maritime Data

Μaragoudakis

2019

Algorithms

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“…The original purpose of AIS was solely collision avoidance but many other applications have since developed. In the scientific literature, the following uses have been identified: ship surveillance, tracking and security, 53,54 collision avoidance and decision support, 55,56 discovery of traffic patterns, [57][58][59][60] traffic simulation, 61,62 ship routing development, 63 risk analysis, [64][65][66][67] mission estimation, 68,69 impact on marine ecology of shipping traffic, 70 accident investigation, 71,72 maritime spatial planning, 73 and ship performance estimation. 33,74 For the present study, AIS data from the period 2007 to 2016 is used.…”

Section: Engineering Approach Reflecting Ship Performance In Icementioning

confidence: 99%

Toward a hybrid model of ship performance in ice suitable for route planning purpose

Montewka

Goerlandt

Lensu

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part O:

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Practical knowledge about the performance of a ship while navigating in ice is crucial for the selection of safe and efficient route for a ship. Existing route finding tools estimate ship performance in ice adopting numerous approaches, ranging from model tests and engineering models to experts-based guidelines. Therein ship performance is usually understood as attainable ship speed or the average speed in given ice conditions; rarely the probability of besetting in ice is taken into account. Those models despite being fairly accurate in the theory share the same shortcoming in practice. The latter encompasses three main issues: (1) inaccurate information about prevailing ice conditions, (2) presence of ice conditions that goes beyond the scope of the models, and (3) the effect of operational patterns and traffic organization on the performance of an individual ship. To approach those issues, we propose a hybrid model of ship performance in ice-covered waters. The hybrid model combines two other sub-models: engineering and data-driven. The former determines ship speed and besetting probability in ridged ice field with ice concentration close to 100%. The latter sub-model provides information on ship's speed in the actual ice conditions, where the speed is affected also by operational restrictions and icebreaker assistance. It is based on an extensive dataset combining ship data from automatic identification system and ice data from ice charts and ice forecast models. The presented hybrid model is valid for a specific ship type, which is ice going bulk carrier (IA Super ice class), operating within the Northern Baltic Sea winter navigation system. The obtained results reveal that the hybrid model in principle is capable of providing reliable information about the performance of a ship in a wide range of conditions accounting for environmental variability and existing operational conditions. The model is suitable for the purpose of safe route planning in ice for a single ship or group of similar ships, accounting for the economy and safety of a voyage.

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“…It can also be used for automatic reporting in areas of mandatory and voluntary reporting. Applications such as vessel tracking [7], [8], [9]; extraction of knowledge [10]; vessel behavior identification [11], [12], [13]; anomaly detection on vessel movements [14], [15], [16]; ship surveillance, tracking and security [17]; discovery of traffic patterns [18]; traffic simulation [19]; accident analysis [20]; ship routing development [21]; near miss detection [22]; collision risk p.2 assessment [23]; exhaust emission estimation [24]; ecological impact analysis [25]; and maritime spatial planning [26] have also been proposed.…”

Section: Introductionmentioning

confidence: 99%

Towards a secure automatic identification system (AIS)

Goudossis

Katsikas

2018

J Mar Sci Technol

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The Automatic Identification System (AIS) is the emerging system for automatic traffic control and collision avoidance services in the maritime transportation sector. It is one of the cornerstone systems for improved marine domain awareness and is embedded in e-navigation, e-bridging, and autonomous ships proposals. However, AIS has some security vulnerabilities, that can be exploited to invade privacy of passengers, to launch intentional collision attacks by pirates and terrorists, etc. In this work, we explore how Identity-Based Public Cryptography and Symmetric Cryptography may enhance the security properties of the AIS.

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A quantitative approach for delineating principal fairways of ship passages through a strait

Cited by 44 publications

References 49 publications

Data Analysis, Simulation and Visualization for Environmentally Safe Maritime Data

Data Analysis, Simulation and Visualization for Environmentally Safe Maritime Data

Toward a hybrid model of ship performance in ice suitable for route planning purpose

Towards a secure automatic identification system (AIS)

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