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.

scholarly journals Information Unfitness of AIS

2012 ◽  
Vol 19 (1) ◽  
pp. 17-24 ◽  
Author(s):  
Andrzej Felski ◽  
Krzysztof Jaskólski
Keyword(s):  
Decision Making ◽  
Collision Avoidance ◽  
Technical Specification ◽  
Supplementary Information ◽  
Radar Measurement ◽  
Dynamic Data ◽  
Inconsistent Data

Abstract Commonly used AIS devices on the ships covered by SOLAS Convention creates ideas of the use of AIS 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, many of users has opinions with regard to inconsistent AIS dynamic data in the process of decision-making by the officer of the watch. Taking into consideration the recordings of the studies and technical specification of AIS, the results of inconsistent data has been analysed in the context of collision avoidance

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 Ship-Collision Avoidance Decision-Making Learning of Unmanned Surface Vehicles with Automatic Identification System Data Based on Encoder—Decoder Automatic-Response Neural Networks

2020 ◽  
Vol 8 (10) ◽  
pp. 754
Author(s):  
Miao Gao ◽  
Guo-You Shi
Keyword(s):  
Neural Networks ◽  
Decision Making ◽  
Time Series ◽  
Collision Avoidance ◽  
Time Series Data ◽  
Series Data ◽  
Automatic Identification ◽  
Identification System ◽  
Automatic Response ◽  
Ship Collision

Intelligent unmanned surface vehicle (USV) collision avoidance is a complex inference problem based on current navigation status. This requires simultaneous processing of the input sequences and generation of the response sequences. The automatic identification system (AIS) encounter data mainly include the time-series data of two AIS sets, which exhibit a one-to-one mapping relation. Herein, an encoder–decoder automatic-response neural network is designed and implemented based on the sequence-to-sequence (Seq2Seq) structure to simultaneously process the two AIS encounter trajectory sequences. Furthermore, this model is combined with the bidirectional long short-term memory recurrent neural networks (Bi-LSTM RNN) to obtain a network framework for processing the time-series data to obtain ship-collision avoidance decisions based on big data. The encoder–decoder neural networks were trained based on the AIS data obtained in 2018 from Zhoushan Port to achieve ship collision avoidance decision-making learning. The results indicated that the encoder–decoder neural networks can be used to effectively formulate the sequence of the collision avoidance decision of the USV. Thus, this study significantly contributes to the increased efficiency and safety of maritime transportation. The proposed method can potentially be applied to the USV technology and intelligent collision-avoidance systems.

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 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 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 Automatic Identification System (AIS) Dynamic Data Integrity Monitoring and Trajectory Tracking Based on the Simultaneous Localization and Mapping (SLAM) Process Model

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8430
Author(s):  
Krzysztof Jaskólski ◽  
Łukasz Marchel ◽  
Andrzej Felski ◽  
Marcin Jaskólski ◽  
Mariusz Specht
Keyword(s):  
Process Model ◽  
Dead Reckoning ◽  
Simultaneous Localization And Mapping ◽  
Process Models ◽  
Automatic Identification ◽  
Identification System ◽  
Dynamic Data ◽  
Integrity Monitoring ◽  
Automatic Identification System ◽  
Localization And Mapping

To enhance the safety of marine navigation, one needs to consider the involvement of the automatic identification system (AIS), an existing system designed for ship-to-ship and ship-to-shore communication. Previous research on the quality of AIS parameters revealed problems that the system experiences with sensor data exchange. In coastal areas, littoral AIS does not meet the expectations of operational continuity and system availability, and there are areas not covered by the system. Therefore, in this study, process models were designed to simulate the tracking of vessel trajectories, enabling system failure detection based on integrity monitoring. Three methods for system integrity monitoring, through hypotheses testing with regard to differences between model output and actual simulated vessel positions, were implemented, i.e., a Global Positioning System (GPS) ship position model, Dead Reckoning and RADAR Extended Kalman Filter (EKF)—Simultaneous localization and mapping (SLAM) based on distance and bearing to navigational aid. The designed process models were validated on simulated AIS dynamic data, i.e., in a simulated experiment in the area of Gdańsk Bay. The integrity of AIS information was determined using stochastic methods based on Markov chains. The research outcomes confirmed the usefulness of the proposed methods. The results of the research prove the high level (~99%) of integrity of the dynamic information of the AIS system for Dead Reckoning and the GPS process model, while the level of accuracy and integrity of the position varied depending on the distance to the navigation aid for the RADAR EKF-SLAM process model.

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

scholarly journals Automatic Identification System (AIS) dynamic data estimation based on discrete Kalman Filter (KF) algorithm

2017 ◽  
pp. 1-1 ◽  
Author(s):  
Krzysztof Jaskólski
Keyword(s):  
Kalman Filter ◽  
Motion Tracking ◽  
Data Availability ◽  
Automatic Identification ◽  
Identification System ◽  
Data Link ◽  
Dynamic Data ◽  
Automatic Identification System ◽  
Safety Reason ◽  
Limit Probability

Due to the safety reason, the ship movement on the littoral area should be monitored, tracked, recorded and stored. Automatic Identification System (AIS) is the perfect tool to ensure this requirement. The limit probability for the AIS dynamic data availability can be limited by the lack of Global Position System (GPS) signal, heading (HDG) and rate of turn (ROT) data in position report. Availability of data link is an additional limitation. For this purpose, it is possible to attach the Discrete Kalman filter (KF) for the position, and course estimation. Coordinate estimation in the absence of a transmission link can improve the quality of AIS service at Vessel Traffic Service (VTS) stations. This article presents Kalman filtering algorithm to improve the possibilities of ship motion tracking and monitoring in the TSS (Traffic Separation Scheme) and fairways area. Only 39 iterations were presented to familiarize how the Kalman filter algorithm works. The archival data from 2006 were used deliberately. During that time, there were problems with the AIS availability service. With the use of measurements series from those years, it is easier to observe the effectiveness of Kalman filter in absence of AIS data.

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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