scholarly journals AIS Politics: The Contested Use of Vessel Tracking at the EU’s Maritime Frontier

2019 ◽  
Vol 44 (5) ◽  
pp. 881-899 ◽  
Author(s):  
Lorenzo Pezzani ◽  
Charles Heller
Keyword(s):  
Mediterranean Sea ◽  
Collision Avoidance ◽  
Tracking System ◽  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Vessel Tracking ◽  
Collision Avoidance System ◽  
The Mediterranean ◽  
Do So

Automatic identification system (AIS) is a vessel tracking system, which since 2004 has become a global tool for the detection and analysis of seagoing traffic. In this article, we look at how this technology, initially designed as a collision avoidance system, has recently become involved in debates concerning migration across the Mediterranean Sea. In particular, after having briefly discussed its emergence and characteristics, we examine how through different practices of (re)appropriation AIS, and the data it generate, have been seized upon, both to contest and to sustain the exclusionary nature of borders, and the mass dying of migrants at sea to which it leads. We do so by referring to forms of data activism we have contributed to in the frame of our Forensic Oceanography project as well as to situations in which AIS has been mobilized by xenophobic groups to demand even stronger exclusionary measures. At the same time, we point to the multiplicity of actors who participate in the politics of migration through AIS in unexpected ways. We conclude by highlighting the irreducible ambivalence of practices of appropriation and call for persistent attention to one’s own positioning within the global datascape constituted by AIS and other data.

scholarly journals Information unfitness as a factor constraining Automatic Identification System (AIS) application to anti-collision manoeuvring

2012 ◽  
Vol 19 (3) ◽  
pp. 60-64 ◽  
Author(s):  
Andrzej Felski ◽  
Krzysztof Jaskólski
Keyword(s):  
Decision Making ◽  
Collision Avoidance ◽  
Significant Role ◽  
Technical Specification ◽  
Supplementary Information ◽  
Automatic Identification ◽  
Identification System ◽  
Radar Measurement ◽  
Dynamic Data ◽  
Automatic Identification System

ABSTRACT Common use of shipboard AIS creates conditions for the use of a new kind of dynamic data in the situation of the risk of collision. AIS position report is a source of supplementary information derived from error leveraged radar measurement. However, in view of the results of the studies there are opinions with regard to inconsistent AIS dynamic data in the process of decision-making by the officer of the watch. By taking into consideration the recordings of the studies and technical specification of AIS it can be concluded that the results of inconsistent data have significant role in collision avoidance manoeuvring.

The ‘ALVA CAPE’ and the Automatic Identification System: The Use of VHF in Collision Avoidance at Sea

2002 ◽  
Vol 55 (3) ◽  
pp. 431-442 ◽  
Author(s):  
S. J. Harding
Keyword(s):  
Case Studies ◽  
Collision Avoidance ◽  
Samuel Johnson ◽  
Automatic Identification ◽  
Identification System ◽  
Controversial Issues ◽  
Automatic Identification System ◽  
Radio Technology ◽  
Marine Navigation

One of the most controversial issues relating to marine navigation is the efficacy of ships' crews using VHF radio technology for bridge-to-bridge communications to agree manoeuvres. Through a re-evaluation of historic case studies, this paper provides background on the development of applying VHF technology in collision avoidance and the legislation, national and international, underpinning the practice; a practice that has found little or no support from the legal establishment. Finally the consequential development of a policy to require specific VHF technology to be installed on ships to facilitate agreements in relation to collision avoidance manoeuvres will be reviewed, that is the Automatic Identification System (AIS).Integrity without knowledge is weak and useless, and knowledge without integrity is dangerous and dreadful. Samuel Johnson

scholarly journals Comprehensive Assessment of Automatic Identification System (AIS) Data Application to Anti-collision Manoeuvring

2015 ◽  
Vol 68 (4) ◽  
pp. 697-717 ◽  
Author(s):  
Andrzej Felski ◽  
Krzysztof Jaskólski ◽  
Paweł Banyś
Keyword(s):  
Collision Avoidance ◽  
Ship Motion ◽  
Supplementary Information ◽  
Automatic Identification ◽  
Identification System ◽  
Radio Communication ◽  
Dynamic Information ◽  
Automatic Identification System ◽  
Ideal System ◽  
Motion Parameters

The use of radar information for collision avoidance is common, however it is effective only for constant values of ship motion parameters. As information delays or information errors occur, it is reasonable to supplement the information derived from radar with another information system. An ideal system should operate automatically and continuously. A system that appears to be suitable to provide this kind of information is the Automatic Identification System (AIS), which may be classified as a radio communication system that uses radio waves to transmit data with regard to ship motion parameters. In this paper the topic of integrity and completeness of AIS information is discussed and the research results for the completeness and integrity of dynamic information are presented. In addition, the outcomes of AIS information correctness from the Gulf of Gdańsk were compared with studies carried out in the Baltic Sea, east of Bornholm, between Trelleborg and Arkona. The results of research for AIS dynamic information with the highest completeness (Position, Course over Ground and Speed over Ground) are presented. The research outcomes presented in the paper lead to the conclusion that AIS could deliver useful supplementary information in the process of collision avoidance.

scholarly journals Navigation Situation Clustering Model of Human-Operated Ships for Maritime Autonomous Surface Ship Collision Avoidance Tests

2021 ◽  
Vol 9 (12) ◽  
pp. 1458
Author(s):  
Taewoong Hwang ◽  
Ik-Hyun Youn
Keyword(s):  
Collision Avoidance ◽  
Automatic Identification ◽  
Identification System ◽  
The West ◽  
Test Environment ◽  
Clustering Model ◽  
Data Driven Approach ◽  
Ship Collision ◽  
Collision Avoidance System ◽  
Autonomous Ship

The collision avoidance system is one of the core systems of MASS (Maritime Autonomous Surface Ships). The collision avoidance system was validated using scenario-based experiments. However, the scenarios for the validation were designed based on COLREG (International Regulations for Preventing Collisions at Sea) or are arbitrary. Therefore, the purpose of this study is to identify and systematize objective navigation situation scenarios for the validation of autonomous ship collision avoidance algorithms. A data-driven approach was applied to collect 12-month Automatic Identification System data in the west sea of Korea, to extract the ship’s trajectory, and to hierarchically cluster the data according to navigation situations. Consequently, we obtained the hierarchy of navigation situations and the frequency of each navigation situation for ships that sailed the west coast of Korea during one year. The results are expected to be applied to develop a collision avoidance test environment for MASS.

scholarly journals A Novel Method for Risk Assessment and Simulation of Collision Avoidance for Vessels based on AIS

Algorithms ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 204 ◽  
Author(s):  
ManhCuong Nguyen ◽  
Shufang Zhang ◽  
Xiaoye Wang
Keyword(s):  
Mathematical Model ◽  
Risk Assessment ◽  
Collision Avoidance ◽  
Warning System ◽  
Automatic Identification ◽  
Identification System ◽  
Novel Method ◽  
Ship Collision ◽  
Collision Avoidance System ◽  
Traffic Detection

The identification of risks associated with collision for vessels is an important element in maritime safety and management. A vessel collision avoidance system is a topic that has been deeply studied, and it is a specialization in navigation technology. The automatic identification system (AIS) has been used to support navigation, route estimation, collision prediction, and abnormal traffic detection. This article examined the main elements of ship collision, developed a mathematical model for the risk assessment, and simulated a collision assessment based on AIS information, thereby providing meaningful recommendations for crew training and a warning system, in conjunction with the AIS on board.

scholarly journals Comparison Of AIS-Based Prediction Of The Distance At The CPA With Factual Separation Between Vessels

2014 ◽  
Vol 21 (1) ◽  
pp. 5-18 ◽  
Author(s):  
Paweł Banyś ◽  
Frank Heymann ◽  
Evelin Engler ◽  
Thoralf Noack
Keyword(s):  
Collision Avoidance ◽  
Incomplete Data ◽  
Data Integrity ◽  
Present Form ◽  
Automatic Identification ◽  
Identification System ◽  
Traffic Situation ◽  
Automatic Identification System ◽  
Research Activities ◽  
Rule Out

Abstract Since its deployment in 2004, the Automatic Identification System (AIS) has been considered a significant improvement of watchkeeping duties at sea. According to current regulations, AIS has not been recognised as an approved anticollision instrument yet. However, it would be difficult to rule out a possibility that AIS, being an essential part of the onboard SOLAS — compliant configuration, is unaidedly used for collision avoidance tasks. Recent research activities of DLR's Department of Nautical Systems have shown that AIS transmissions may contain a lot of incomplete data and the system does not have any dependable information on its data integrity. For that reason, the computation of the closest point of approach (CPA) and the time to the CPA (TCPA) are analysed based on AIS data involving multiple vessels, in order to compare the predictions with factual approaches between vessels and to evaluate the usability of AIS data, in its present form, for the appraisal of the traffic situation around each vessel.

scholarly journals Using AIS to Attempt a Quantitative Evaluation of Unobserved Trawling Activity in the Mediterranean Sea

2020 ◽  
Vol 7 ◽  
Author(s):  
Carmen Ferrà ◽  
Anna Nora Tassetti ◽  
Enrico Nicola Armelloni ◽  
Alessandro Galdelli ◽  
Giuseppe Scarcella ◽  
...  
Keyword(s):  
Mediterranean Sea ◽  
Fishing Effort ◽  
Automatic Identification ◽  
Identification System ◽  
The Past ◽  
Research Fields ◽  
The Mediterranean ◽  
Maritime Spatial Planning ◽  
Maritime Domain Awareness ◽  
Bottom Trawler

In the past decades, the Automatic Identification System (AIS) has been employed in numerous research fields as a valuable tool for, among other things, Maritime Domain Awareness and Maritime Spatial Planning. In contrast, its use in fisheries management is hampered by coverage and transmission gaps. Transmission gaps may be due to technical limitations (e.g., weak signal or interference with other signals) or to deliberate switching off of the system, to conceal fishing activities. In either case such gaps may result in underestimating fishing effort and pressure. This study was undertaken to map and analyze bottom trawler transmission gaps in terms of duration and distance from the harbor with a view to quantifying unobserved fishing and its effects on overall trawling pressure. Here we present the first map of bottom trawler AIS transmission gaps in the Mediterranean Sea and a revised estimate of fishing effort if some gaps are considered as actual fishing.

scholarly journals De-Collision Algorithm for AIS for Multi-User on Single Satellite Antenna

2019 ◽  
Vol 8 (6) ◽  
pp. 801-805
Keyword(s):  
Collision Avoidance ◽  
Viterbi Algorithm ◽  
Mean Shift ◽  
Automatic Identification ◽  
Identification System ◽  
Satellite Antenna ◽  
Automatic Identification System ◽  
Shift Keying ◽  
Collision Mitigation ◽  
Navigational Systems

The Automatic Identification System (AIS), acquired popularity and preferences to be deployed in navigational systems for collision avoidance due to wider coverage. The recently developed satellite AIS provides better precision than the earlier employed Terrestrial AIS. Satellite AIS technology utilizes Gaussian Mean Shift Keying (GMSK) to modulate the message. The modulated AIS message is then transmitted and received between ships and satellite AIS over SOTDMA channel. The conventional single axis satellite AIS transceiver failed to decode the message accurately due to message overlap. In earlier work 3-AIS trans-receiver was developed to reduce the chance of message collision; however, system became bulky and complex. In this paper, collision mitigation algorithm is developed and the single axis transceiver is retained. Thus the complexity is reduced greatly and collision is eliminated as well. Hard Viterbi Algorithm developed in this work corrects the overlapped AIS message for proper decoding of the received messages. The transmitter, receiver and Viterbi algorithm are designed in VHDL Language and simulation of all blocks is performed in Eldo Simulator

Mapping Global Shipping Density from AIS Data

2016 ◽  
Vol 70 (1) ◽  
pp. 67-81 ◽  
Author(s):  
Lin Wu ◽  
Yongjun Xu ◽  
Qi Wang ◽  
Fei Wang ◽  
Zhiwei Xu
Keyword(s):  
Collision Avoidance ◽  
Reporting System ◽  
Data Retrieval ◽  
Traffic Density ◽  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Identity Information ◽  
Density Maps ◽  
Ship Tracks

Mapping global shipping density, including vessel density and traffic density, is important to reveal the distribution of ships and traffic. The Automatic Identification System (AIS) is an automatic reporting system widely installed on ships initially for collision avoidance by reporting their kinematic and identity information continuously. An algorithm was created to account for errors in the data when ship tracks seem to ‘jump’ large distances, an artefact resulting from the use of duplicate identities. The shipping density maps, including the vessel and traffic density maps, as well as AIS receiving frequency maps, were derived based on around 20 billion distinct records during the period from August 2012 to April 2015. Map outputs were created in three different spatial resolutions: 1° latitude by 1° longitude, 10 minutes latitude by 10 minutes longitude, and 1 minute latitude by 1 minute longitude. The results show that it takes only 56 hours to process these records to derive the density maps, 1·7 hours per month on average, including data retrieval, computation and updating of the database.

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