scholarly journals Performance Analysis of a Medium Frequency Offshore Grid for Identification Of Vessels Sailing on High Density Maritime European Routes

2017 ◽  
Vol 24 (4) ◽  
pp. 18-26
Author(s):  
Alfonso López ◽  
Miguel Gutiérrez ◽  
Andrés Ortega ◽  
Cristina Puente ◽  
Alejandro Morales ◽  
...  
Keyword(s):  
Grid Method ◽  
Real Data ◽  
Satellite System ◽  
Simulation Software ◽  
High Density ◽  
Traffic Density ◽  
Automatic Identification ◽  
Identification System ◽  
Distributed Data ◽  
Medium Frequency

Abstract The paper analyses the performance of an Automatic Vessel Identification System on Medium Frequency (AVISOMEF), which works with the Grid Method (GM) on high density maritime European routes using real data and uniformly distributed data. Compared to other systems, AVISOMEF is a novelty, as it is not a satellite system, nor is it limited by a given coverage distance, in contrast to the Automatic Identification System (AIS), though in exceptional circumstances it leans towards it. To perform the analysis, special simulation software was developed. Moreover, a number of maritime routes along with their traffic density data were selected for the study. For each route, two simulations were performed, the first of which based on the uniform traffic distribution along the route, while the second one made use of real AIS data positioning of vessels sailing on the selected routes. The obtained results for both simulations made the basis for formulating conclusions regarding the capacity of selected routes to support AVISOMEF.

Ship Trajectories Pre-processing Based on AIS Data

2018 ◽  
Vol 71 (5) ◽  
pp. 1210-1230 ◽  
Author(s):  
Liangbin Zhao ◽  
Guoyou Shi ◽  
Jiaxuan Yang
Keyword(s):  
Data Mining ◽  
Traffic Density ◽  
Automatic Identification ◽  
Identification System ◽  
Traffic Data ◽  
Density Maps ◽  
Different Types ◽  
Quality Dimensions ◽  
Time Accuracy

Data derived from the Automatic Identification System (AIS) plays a key role in water traffic data mining. However, there are various errors regarding time and space. To improve availability, AIS data quality dimensions are presented for detecting errors of AIS tracks including physical integrity, spatial logical integrity and time accuracy. After systematic summary and analysis, algorithms for error pre-processing are proposed. Track comparison maps and traffic density maps for different types of ships are derived to verify applicability based on the AIS data from the Chinese Zhoushan Islands from January to February 2015. The results indicate that the algorithms can effectively improve the quality of AIS trajectories.

Securing the Automatic Identification System (AIS): Using public key cryptography to prevent spoofing whilst retaining backwards compatibility

2021 ◽  
pp. 1-13
Author(s):  
Gareth Wimpenny ◽  
Jan Šafář ◽  
Alan Grant ◽  
Martin Bransby
Keyword(s):  
Data Exchange ◽  
Situational Awareness ◽  
Public Key Cryptography ◽  
Satellite System ◽  
Public Key ◽  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Safe Navigation ◽  
Global Navigation Satellite

Abstract The civilian Automatic Identification System (AIS) has no inherent protection against spoofing. Spoofed AIS messages have the potential to interfere with the safe navigation of a vessel by, amongst other approaches, spoofing maritime virtual aids to navigation and/or differential global navigation satellite system (DGNSS) correction data conveyed across it. Acting maliciously, a single transmitter may spoof thousands of AIS messages per minute with the potential to cause considerable nuisance; compromising information provided by AIS intended to enhance the mariner's situational awareness. This work describes an approach to authenticate AIS messages using public key cryptography (PKC) and thus provide unequivocal evidence that AIS messages originate from genuine sources and so can be trusted. Improvements to the proposed AIS authentication scheme are identified which address a security weakness and help avoid false positives to spoofing caused by changes to message syntax. A channel loading investigation concludes that sufficient bandwidth is available to routinely authenticate all AIS messages whilst retaining backwards compatibility by carrying PKC ‘digital signatures’ in a separate VHF Data Exchange System (VDES) side channel.

scholarly journals Distributed Stochastic Search Algorithm for Multi-ship Encounter Situations

2017 ◽  
Vol 70 (4) ◽  
pp. 699-718 ◽  
Author(s):  
Donggyun Kim ◽  
Katsutoshi Hirayama ◽  
Tenda Okimoto
Keyword(s):  
Distributed Algorithms ◽  
Search Algorithm ◽  
Real Data ◽  
Stochastic Search ◽  
Automatic Identification ◽  
Identification System ◽  
Local Search Algorithm ◽  
Ship Collision ◽  
Stochastic Search Algorithm ◽  
Made In

Ship collision avoidance involves helping ships find routes that will best enable them to avoid a collision. When more than two ships encounter each other, the procedure becomes more complex since a slight change in course by one ship might affect the future decisions of the other ships. Two distributed algorithms have been developed in response to this problem: Distributed Local Search Algorithm (DLSA) and Distributed Tabu Search Algorithm (DTSA). Their common drawback is that it takes a relatively large number of messages for the ships to coordinate their actions. This could be fatal, especially in cases of emergency, where quick decisions should be made. In this paper, we introduce Distributed Stochastic Search Algorithm (DSSA), which allows each ship to change her intention in a stochastic manner immediately after receiving all of the intentions from the target ships. We also suggest a new cost function that considers both safety and efficiency in these distributed algorithms. We empirically show that DSSA requires many fewer messages for the benchmarks with four and 12 ships, and works properly for real data from the Automatic Identification System (AIS) in the Strait of Dover.

scholarly journals A Vessel Positioning Algorithm Based on Satellite Automatic Identification System

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Shexiang Ma ◽  
Jie Wang ◽  
Xin Meng ◽  
Junfeng Wang
Keyword(s):  
Satellite System ◽  
Automatic Identification ◽  
Identification System ◽  
Multiple Model ◽  
Additional Measurement ◽  
Automatic Identification System ◽  
Interactive Multiple Model ◽  
Global Navigation Satellite ◽  
Positioning Algorithm ◽  
Model Algorithm

Vessels can obtain high precision positioning by using the global navigation satellite system (GNSS), but when the ship borne GNSS receiver fails, the existence of an alternative positioning system is important for the navigation safety of vessel. In this paper, a localization method based on the signals transmitted by satellite-based automatic identification system (AIS) is proposed for vessel in GNSS-denied environments. In the proposed method, the positioning model is a modification on the basis of time difference and frequency difference of arrival measurements by introducing an additional measurement, and the measurement is obtained through the interactive multiple model algorithm. The performance of the proposed strategy is evaluated through simulations, and the results validate the feasibility and reliability of vessel localization based on satellite-based AIS.

scholarly journals Virtual Electronic Aids to Navigation for Remote and Ecologically Sensitive Regions

2016 ◽  
Vol 70 (2) ◽  
pp. 225-241 ◽  
Author(s):  
R. Glenn Wright ◽  
Michael Baldauf
Keyword(s):  
Denial Of Service ◽  
Satellite System ◽  
The Arctic ◽  
Automatic Identification ◽  
Identification System ◽  
Digital Information ◽  
Hostile Environment ◽  
Ship Navigation ◽  
Potential Methods ◽  
Global Navigation Satellite

Vessel traffic in the Arctic is expanding in volume both within and transiting the region, yet the infrastructure necessary to support modern ship navigation is lacking. This includes aids to navigation such as buoys and beacons that can be difficult to place and maintain in this hostile environment that stretches across vast distances. The results of research are described which determine whether virtual electronic Aids to Navigation (eAtoN) existing entirely as digital information objects can overcome the practical limitations of physical aids to navigation (AtoN) and Automatic Identification System (AIS) radio eAtoN. Capabilities unique to virtual eAtoN that are not available using either physical or AIS radio technologies are also examined including dynamic and real time properties and immunity to Global Navigation Satellite System (GNSS) and AIS spoofing, aliasing, denial of service attacks and service outages. Conclusions are provided describing potential methods of deployment based upon similar concepts already in use.

SPECIALIZED MEASURES OF LEAF OUTLINES AND HIERARCHICAL PERCEPTRONS IN AN AUTOMATIC IDENTIFICATION OF PLANTS

2004 ◽  
Vol 15 (08) ◽  
pp. 1171-1186 ◽  
Author(s):  
WOJCIECH BORKOWSKI ◽  
LIDIA KOSTRZYŃSKA
Keyword(s):  
Neural Network ◽  
Nearest Neighbor ◽  
Real Data ◽  
Automatic Identification ◽  
Identification System ◽  
Data Sets ◽  
Identification Algorithm ◽  
Plant Identification ◽  
Neural Network Classifiers ◽  
Computer Identification

The development of an efficient image-based computer identification system for plants or other organisms is an important ambitious goal, which is still far from realization. This paper presents three new methods potentially usable for such a system: fractal-based measures of complexity of leaf outline, a heuristic algorithm for automatic detection of leaf parts — the blade and the petiole, and a hierarchical perceptron — a kind of neural network classifier. The next few sets of automatically extractable features of leaf blades, encompassed those presented and/or traditionally used, are compared in the task of plant identification using the simplest known "nearest neighbor" identification algorithm, and more realistic neural network classifiers, especially the hierarchical. We show on two real data sets that the presented techniques are really usable for automatic identification, and are worthy of further investigation.

scholarly journals How can Automatic Identification System (AIS) data be used for maritime spatial planning?

2018 ◽  
Author(s):  
Matthieu Le Tixerant ◽  
Damien Le Guyader ◽  
Françoise Gourmelon ◽  
Betty Queffelec
Keyword(s):  
Spatial Planning ◽  
Legal Framework ◽  
Traffic Density ◽  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Legal Questions ◽  
Pertinent Data ◽  
Spatio Temporal ◽  
Maritime Spatial Planning

Although the importance of Maritime Spatial Planning (MSP) as a concept is know acknowledged and the legal framework is in place, the task of applying it remains a delicate one. One of the keys to success is having pertinent data. Knowing how maritime uses unfold in a spatio-temporal context, and what conflicting or synergistic interactions exist between activities, is crucial. However, this information is especially hard to obtain in a marine environment. As a result this information has often been identified as the missing layer in information systems developed by maritime stakeholders. Since 2002, the Automatic Identification System (AIS) has been undergoing a major development. Allowing for real time geo-tracking and identification for equipped vessels, the data that issues from AIS data promises to map and describe certain marine human activities.After recapitulating the main characteristics of AIS and the data it provides, this article proposes to evaluate how AIS is currently used in MSP at a European level, and to concisely present a series of methods and results obtained within the framework of several operational research projects. The objective is to illustrate how the AIS data processing and analysis can produce adequate information for MSP: maritime traffic density, shipping lanes and navigation flows, hierarchical network of maritime routes, alleged fishing zones, spatio-temporal interactions between activities (potential conflicting uses or synergies). The conclusion looks in particular at the legal questions concerning the use of AIS.

scholarly journals Mapping Marine Traffic Density by Using AIS Data: An Application in the Northern Aegean Sea

2018 ◽  
Vol 25 (4) ◽  
pp. 49-58 ◽  
Author(s):  
Burak Kundakçi ◽  
Selçuk Nas
Keyword(s):  
Data Storage ◽  
Aegean Sea ◽  
Traffic Density ◽  
Automatic Identification ◽  
Identification System ◽  
Cross Sectional ◽  
Marine Traffic ◽  
Desktop Application ◽  
Intersection Algorithm ◽  
Northern Aegean Sea

Abstract Automatic Identification System (AIS) data is used for monitoring the movements of vessels live movements through instant transmission of vessel information while, at the same time, historical AIS data is used for marine traffic analysis by researchers. There are several methods and computer programs developed for the analysis of marine traffic by the use of AIS data. Combining the intersection algorithm proposed by Antonio (1992) and distance calculation method, this study develops a method to analyse vessel distribution on a selected cross sectional line (SCS) in the Northern Aegean Sea. As a complementary to the new methods proposed, a desktop application is developed in C# programming language to visualize the vessel distribution on the SCS line. SQL server is used for AIS data storage and analysis. The study is conducted over 7-day AIS data, specifically 2.382.469 rows and 42.884.442 data in total, belonging to the Northern Aegean Sea marine traffic. As a result, the mapping of the movements of different types of vessels in the Northern Aegean Sea is effectively performed and Frequency-Distance, Draught-Distance, SOG-Distance, SOG-COG distributions on the SCS line are successfully analysed by the new method introduced.

scholarly journals Multiobjective Route Selection Based on LASSO Regression: When Will the Suez Canal Lose Its Importance?

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Jingmiao Zhou ◽  
Yuzhe Zhao ◽  
Jiayan Liang
Keyword(s):  
Real Data ◽  
Suez Canal ◽  
Automatic Identification ◽  
Identification System ◽  
Route Selection ◽  
Lasso Regression ◽  
Fuel Price ◽  
Cape Of Good Hope ◽  
Weighted Sum Method ◽  
Multiobjective Particle Swarm Optimization

With coronavirus disease 2019 reshaping the global shipping market, many ships in the Europe-Asia trades that need to sail through the Suez Canal begun to detour via the much longer route, the Cape of Good Hope. In order to explain and predict the route choice, this paper employs the least absolute shrinkage and selection operator regression to estimate fuel consumption based on the automatic identification system and ocean dataset and designed a multiobjective particle swarm optimization to find Pareto optimal solutions that minimize the total voyage cost and total voyage time. After that, the weighted sum method was introduced to deal with the route selection. Finally, a case study was conducted on the real data from CMA CGM, a leading worldwide shipping company, and four scenarios of fuel prices and charter rates were built and analyzed. The results show that the detour around the Cape of Good Hope is preferred only in the scenario of low fuel price and low charter. In addition, the paper suggests that the authority of Suez Canal should cut down the canal toll according to our result to win back the ships because we have verified that offering a discount on the canal roll is effective.

scholarly journals Multi-Criteria Selection of Surface Units for SAR Operations at Sea Supported by AIS Data

2021 ◽  
Vol 13 (16) ◽  
pp. 3151
Author(s):  
Miroslaw Wielgosz ◽  
Marzena Malyszko
Keyword(s):  
Selection Process ◽  
Traffic Density ◽  
Automatic Identification ◽  
Identification System ◽  
Rescue Services ◽  
Expert Analysis ◽  
Electronic Chart ◽  
And Performance ◽  
High Traffic Density ◽  
Selection Of

The authors discuss currently conducted research aimed at improving the planning and performance of search and rescue (SAR) operations at sea. The focus is on the selection of surface units in areas of high traffic density. A large number of ships in the area of distress can make the process of selection of best suited vessels longer. An analysis of features which may render a vessel unsuitable for the job, depending on the area and type of operation, has been conducted. Criteria of assessment and selection of ships have been described, preceded by an expert analysis. The selection process has been made using Multi-Criteria Decision Analysis (MCDA). The authors propose to apply officially available data from the Automatic Identification System (AIS)—a sensor for the ECDIS and other electronic chart systems—in the analysis of the availability of ships. Algorithms filtering available units have been built and applied in a simulation, using real AIS data, of one of the most common types of SAR operations. The method is proposed as an enhancement of decision support systems in maritime rescue services.

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