scholarly journals Simulation of Computation Time of Ship Traffic Analysis using Data Clustering for a Vessel Traffic System

2021 ◽  
Vol 1 (4) ◽  
pp. 41-50
Author(s):  
Rahimuddin ◽  
Mehdi Nakisa ◽  
Haryanti Rivai ◽  
Hasnawiyah Hasan ◽  
Husni Sitepu ◽  
...  
Keyword(s):  
Warning System ◽  
Computation Time ◽  
Critical Issue ◽  
Traffic Analysis ◽  
Automatic Identification ◽  
Identification System ◽  
Ship Traffic ◽  
Traffic System ◽  
The North ◽  
Cluster Area

Indonesian water territory is a crossroads of international shipping lanes connecting countries bordering the South China Sea in the north, countries in southern, and countries from western Indonesia. The shipping route goes through the Sunda Strait, Sumbawa Strait, Makassar Strait and Melaka Strait. The shipping lanes are grouped into three main routes called ALKI (Alur Laut Kepulauan Indonsia) I, II, and III. The increase in total number of ships per year with various capacities tends to increases the traffic in the lane and the risk of ship collision. Using AIS (Automatic Identification System) technology with a warning system required to prevent the effect of accidents. Through the Vessel Traffic System (VTS) receive, record, and analysis the traffic data in the covered area. Computation time become a critical issue for ship traffic assessment in the lane. A numerical simulation program developed and analysed the computation time of ship traffic analysis using cluster area method. The result showed a shorter computation time for a more number of cluster area. The computation time increase quadratically with an increase of ships number or objects.

scholarly journals A comprehensive inventory of ship traffic exhaust emissions in the European sea areas in 2011

2015 ◽  
Vol 15 (5) ◽  
pp. 7459-7491 ◽  
Author(s):  
J.-P. Jalkanen ◽  
L. Johansson ◽  
J. Kukkonen
Keyword(s):  
Assessment Model ◽  
Automatic Identification ◽  
Identification System ◽  
Traffic Emission ◽  
Ship Traffic ◽  
Eu Member States ◽  
The North ◽  
The North Sea ◽  
System Data ◽  
The Mediterranean

Abstract. Emissions originated from ship traffic in European sea areas were modelled using the Ship Traffic Emission Assessment Model (STEAM), which uses Automatic Identification System data to describe ship traffic activity. We have estimated the emissions from ship traffic in the whole of Europe in 2011. We report the emission totals, the seasonal variation, the geographical distribution of emissions, and their disaggregation between various ship types and flag states. The total ship emissions of CO2, NOx, SOx, CO and PM2.5 in Europe for year 2011 were estimated to be 131, 2.9, 1.2, 0.2 and 0.3 million tons, respectively. The emissions of CO2 from Baltic Sea were evaluated to be more than a half (58%) of the emissions of the North Sea shipping; the combined contribution of these two sea regions was almost as high (96%) as the total emissions from ships in the Mediterranean. As expected, the shipping emissions of SOx were significantly lower in the SOx Emission Control Areas, compared with the corresponding values in the Mediterranean. Shipping in the Mediterranean Sea is responsible for 39 and 49% of the European ship emitted CO2 and SOx emissions, respectively. In particular, this study reported significantly smaller emissions of NOx, SOx and CO for shipping in the Mediterranean than the EMEP inventory; however, the reported PM2.5 emissions were in a fairly good agreement with the corresponding values reported by EMEP. The vessels registered to all EU member states are responsible for 55% of the total CO2 emitted by ships in the study area. The vessels under the flags of convenience were responsible for 25% of the total CO2 emissions.

scholarly journals A comprehensive inventory of ship traffic exhaust emissions in the European sea areas in 2011

2016 ◽  
Vol 16 (1) ◽  
pp. 71-84 ◽  
Author(s):  
J.-P. Jalkanen ◽  
L. Johansson ◽  
J. Kukkonen
Keyword(s):  
Assessment Model ◽  
Automatic Identification ◽  
Identification System ◽  
Traffic Emission ◽  
Ship Traffic ◽  
Eu Member States ◽  
The North ◽  
System Data ◽  
The Mediterranean ◽  
The Baltic

Abstract. Emissions originating from ship traffic in European sea areas were modelled using the Ship Traffic Emission Assessment Model (STEAM), which uses Automatic Identification System data to describe ship traffic activity. We have estimated the emissions from ship traffic in the whole of Europe in 2011. We report the emission totals, the seasonal variation, the geographical distribution of emissions, and their disaggregation between various ship types and flag states. The total ship emissions of CO2, NOx, SOx, CO, and PM2.5 in Europe for year 2011 were estimated to be 121, 3.0, 1.2, 0.2, and 0.2 million tons, respectively. The emissions of CO2 from the Baltic Sea were evaluated to be more than a half (55 %) of the emissions of the North Sea shipping; the combined contribution of these two sea regions was almost as high (88 %) as the total emissions from ships in the Mediterranean. As expected, the shipping emissions of SOx were significantly lower in the SOx Emission Control Areas, compared with the corresponding values in the Mediterranean. Shipping in the Mediterranean Sea is responsible for 40 and 49 % of the European ship emitted CO2 and SOx emissions, respectively. In particular, this study reported significantly smaller emissions of NOx, SOx, and CO for shipping in the Mediterranean than the EMEP inventory; however, the reported PM2.5 emissions were in a fairly good agreement with the corresponding values reported by EMEP. The vessels registered to all EU member states are responsible for 55 % of the total CO2 emitted by ships in the study area. The vessels under the flags of convenience were responsible for 25 % of the total CO2 emissions.

scholarly journals Positioning Error Analysis of Ranging-Mode Using AIS Signals in China

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Kai Zheng ◽  
Qing Hu ◽  
Jingbo Zhang
Keyword(s):  
Measurement Errors ◽  
Phase Locking ◽  
Automatic Identification ◽  
Identification System ◽  
Time Of Arrival ◽  
Positioning Error ◽  
North East ◽  
The North ◽  
Error Distributions ◽  
Shift Keying

In order to provide resilient position, navigation, and time (PNT) information forE-Navigation, the ranging-mode (R-Mode) positioning using automatic identification system (AIS) signals is encouraged. As the accuracy is the key for the positioning system, this paper investigates the position error of the R-Mode positioning based on AIS shore-based station in China. The measurement errors of Gaussian filtered minimum shift keying (GMSK) demodulation based on carrier phase locking loop are investigated in theory. The dilution of precision (DOP) for time of arrival (TOA) and time difference of arrival (TDOA) used in R-Mode positioning of AIS is discussed in two measurement mechanisms. The positioning error distributions in the North, East, and South Sea regions of China based on the existing AIS shore-based stations are evaluated. The positioning accuracy is at the meter level in the most traffic dense areas to meet the requirements for vessel navigation.

The Automated Risk Estimation for the Navigation of Autonomous Ships by Learning with Navigation Feature

2020 ◽  
pp. 2041003
Author(s):  
Wei Chian Tan ◽  
Kie Hian Chua ◽  
Yanling Wu
Keyword(s):  
Nearest Neighbor ◽  
Dimensional Space ◽  
Risk Estimation ◽  
Nearest Neighbor Search ◽  
Mathematical Representation ◽  
Automatic Identification ◽  
Identification System ◽  
North West ◽  
The North ◽  
Neighbor Search

This work presents a data-driven approach for the automated risk estimation of the voyage of a vessel or ship. While the industry is moving from a compliance-based framework with existing rules to a risk-based one, there is also a need to monitor the risk of a vessel from the perspective of the navigation. This is of even higher importance for the case of autonomous ships. Built based on the state-of-the-art mathematical representation, the navigation feature, each existing voyage is transformed into a corresponding series of points in [Formula: see text]-dimensional space. During the stage of pre-processing, given a set of historical Automatic Identification System (AIS) data, those records that belong to the same vessel within a certain period of time are taken as a voyage and mapped to the corresponding space of the navigation feature. After the pre-processing and during the online monitoring, the current trajectory of the vessel is transformed into the corresponding representation in the same way. Based on a nearest-neighbor search scheme, the distance from the nearest neighbor is taken as the risk of the current voyage. In other words, the deviation from the closest route in the historical data is taken as the risk. The developed method has demonstrated encouraging performance on a set of challenging historical AIS data from the Australian Maritime Safety Authority, covering three regions in the Australian territory, namely, the Bass Strait, the Great Australian Bight and the North West.

scholarly journals Evaluation of AIS reception in Arctic regions from space by using a stratospheric balloon flight

Polar Record ◽  
2011 ◽  
Vol 48 (1) ◽  
pp. 39-47 ◽  
Author(s):  
Jesper Abildgaard Larsen ◽  
Jens Dalsgaard Nielsen ◽  
Hans Peter Mortensen ◽  
Ulrik Wilken Rasmussen ◽  
Troels Laursen ◽  
...  
Keyword(s):  
Barents Sea ◽  
The Arctic ◽  
Automatic Identification ◽  
Identification System ◽  
Balloon Flight ◽  
Ship Traffic ◽  
Arctic Regions ◽  
Increased Risk ◽  
Stratospheric Balloon

ABSTRACTDue to the increased melting season in the arctic regions, especially in the seas surrounding Greenland, there has been an increased interest in utilising these waterways, both as an efficient transport route and an attractive leisure destination. However, with heavier traffic comes an increased risk of accidents. Due to the immense size and poor infrastructure of Greenland, it is not feasible to deploy ground based ship monitoring stations throughout the Greenland coastline. Thus the only feasible solution is to perform such surveillance from space. In this paper it is shown how it is possible to receive transmissions from the Automatic Identification System (AIS) from space and the quality of the received AIS signal is analysed. To validate the proposed theory, a field study, utilising a prototype of AAUSAT3, the third satellite from Aalborg University, was performed using a stratospheric balloon flight in the northern part of Sweden and Finland during the autumn of 2009. The analysis finds that, assuming a similar ship distribution as in the Barents Sea, it is feasible to monitor the ship traffic around Greenland from space with a satisfactory result.

scholarly journals Extension of an assessment model of ship traffic exhaust emissions for particulate matter and carbon monoxide

2012 ◽  
Vol 12 (5) ◽  
pp. 2641-2659 ◽  
Author(s):  
J.-P. Jalkanen ◽  
L. Johansson ◽  
J. Kukkonen ◽  
A. Brink ◽  
J. Kalli ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Particulate Matter ◽  
Exhaust Emissions ◽  
Sulphur Content ◽  
Assessment Model ◽  
Automatic Identification ◽  
Identification System ◽  
Extended Model ◽  
Engine Load ◽  
Ship Traffic

Abstract. A method is presented for the evaluation of the exhaust emissions of marine traffic, based on the messages provided by the Automatic Identification System (AIS), which enable the positioning of ship emissions with a high spatial resolution (typically a few tens of metres). The model also takes into account the detailed technical data of each individual vessel. The previously developed model was applicable for evaluating the emissions of NOx, SOx and CO2. This paper addresses a substantial extension of the modelling system, to allow also for the mass-based emissions of particulate matter (PM) and carbon monoxide (CO). The presented Ship Traffic Emissions Assessment Model (STEAM2) allows for the influences of accurate travel routes and ship speed, engine load, fuel sulphur content, multiengine setups, abatement methods and waves. We address in particular the modeling of the influence on the emissions of both engine load and the sulphur content of the fuel. The presented methodology can be used to evaluate the total PM emissions, and those of organic carbon, elemental carbon, ash and hydrated sulphate. We have evaluated the performance of the extended model against available experimental data on engine power, fuel consumption and the composition-resolved emissions of PM. We have also compared the annually averaged emission values with those of the corresponding EMEP inventory, As example results, the geographical distributions of the emissions of PM and CO are presented for the marine regions of the Baltic Sea surrounding the Danish Straits.

scholarly journals Predicting Motion Patterns Using Optimal Paths

2021 ◽  
Vol 9 ◽  
Author(s):  
Mads Fromeide ◽  
Alex Hansen
Keyword(s):  
Energy Landscape ◽  
Traffic Analysis ◽  
Moving Object ◽  
Automatic Identification ◽  
Identification System ◽  
End Points ◽  
Motion Patterns ◽  
Automatic Identification System ◽  
Optimal Paths ◽  
Regular Patterns

The ability to navigate safely and efficiently through a given landscape is relevant for any intelligent moving object. Examples range from robotic science and traffic analysis, to the behavior within an ecosystem. Many objects tend to move in patterns depending on their nature. By establishing models of patterns of motion one may estimate the future motion within an area. We propose here a method for detecting regular patterns of motion by modeling the environment as an energy landscape, and locating optimal paths through it. As an example, we use maritime position Automatic Identification System (AIS) data as input to work out optimal routes between different start and end points when these are not located along the standard shipping lanes. These initial tests show that the method has potential for analyzing and determining regular patterns of motion.

scholarly journals Modeling of Vessel Traffic Flow for Waterway Design–Port of Świnoujście Case Study

2021 ◽  
Vol 11 (17) ◽  
pp. 8126
Author(s):  
Agnieszka Nowy ◽  
Kinga Łazuga ◽  
Lucjan Gucma ◽  
Andrej Androjna ◽  
Marko Perkovič ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Traffic Flow ◽  
Probabilistic Models ◽  
Historical Data ◽  
Automatic Identification ◽  
Identification System ◽  
Practical Applications ◽  
Ship Traffic ◽  
Navigation Patterns

The paper presents an analysis of ship traffic using the port of Świnoujście and the problems associated with modelling vessel traffic flows. Navigation patterns were studied using the Automatic Identification System (AIS); an analysis of vessel traffic was performed with statistical methods using historical data; and the paper presents probabilistic models of the spatial distribution of vessel traffic and its parameters. The factors that influence the spatial distribution were considered to be the types of vessels, dimensions, and distances to hazards. The results show a correlation between the standard deviation of the traffic flow, the vessel sizes, and the distance to the hazard. These can be used in practice to determine the safety of navigation and the design of non-existing waterways and to create a general model of vessel traffic flow. The creation of the practical applications is intended to improve navigation efficiency, safety, and risk analysis in any particular area.

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