Marine Traffic Data Clustering for Ships Route Planning

2021 ◽  
Vol 27 (11) ◽  
pp. 607-615
Author(s):  
V. M. Grinyak ◽  
◽  
A. V. Shulenina ◽  
Keyword(s):  
Traffic Control ◽  
Heavy Traffic ◽  
Route Planning ◽  
Weighted Graph ◽  
Tokyo Bay ◽  
Automatic Identification ◽  
Subtractive Clustering ◽  
Analysis Model ◽  
Marine Traffic ◽  
Sea Area

This paper is about maritime safety. The system of vessel traffic schemas is one of the key elements of sea traffic control at the arias with heavy traffic. Such system based on a set of rules and guidelines defined by traffic schemas for certain water areas. From the classic approach, vessels that are not following the guidelines do not necessarily create alarming situations at the moment, however, could lead to complex danger navigation situations with the time passed. The problem of ship route planning through the area with highly intensive traffic is considered in this paper. The importance of the problem becomes more significant these days when taking in account development of self-navigating autonomous vessels. It is expected to respect area navigation limitations while planning vessel path through the areas with identified traffic schema. One of the ways to identify navigation limitations could be trajectory pattern recognition at certain sea areas based on retrospective traffic analysis. Model representation for such task could be based on vessel moving parameters clustering. The presented model is based on solving the shortest path problem on weighted graph. There are several ways to create such weighted graphs are suggested in the paper: regular grid of vertices and edges, layer grid of vertices and edges, random grid of vertices and edges, vertices and edges identified based on retrospective data. All edges are defined as a weighted function of "desirability" of one or another vessel course for each location of sea area with consideration of identified trajectory patterns. For that the area is divided into sub areas where courses and velocity clustering is evaluated. Possible ways of clustering are discussed in the paper and the choice made in favor of subtractive clustering that does not require predefining of cluster count. Automatic Identification Systems (AIS) could be used as data source for the traffic at certain sea areas. The possibility of using AIS data available on specialized public Internet resources is shown in the paper. Although such data typically has low density, they still could well represent vessel traffic features at the certain sea area. In this paper are presenting samples of route panning for Tsugaru Straight ang Tokyo Bay.

scholarly journals DECISION SUPPORT FOR MARINE TRAFFIC CONTROL BASED ON ROUTE CLUSTERING

2020 ◽  
Vol 12 (3) ◽  
pp. 436-449
Author(s):  
Victor M. Grinyak ◽  
◽  
Alexander S. Devyatisilnyi ◽  
Yuryi S. Ivanenko ◽  
◽  
...  
Keyword(s):  
Decision Support ◽  
Traffic Control ◽  
Marine Traffic

scholarly journals Marine Traffic Simulation Using Ship Agent Clusters : Northbound Traffic in Tokyo Bay

2006 ◽  
Vol 115 (0) ◽  
pp. 11-16 ◽  
Author(s):  
Masaaki INAISHI ◽  
Hayato KONDO ◽  
Masaki KONDO ◽  
Akira KAWAGUCHI
Keyword(s):  
Traffic Simulation ◽  
Tokyo Bay ◽  
Marine Traffic

Using AIS Data for Navigational Risk Assessment in Restricted Waters

2013 ◽  
pp. 245-254
Author(s):  
Adi Maimun ◽  
Istaz F. Nursyirman ◽  
Ang Yit Sian ◽  
Rahimuddin Samad ◽  
Sulaiman Oladokun
Keyword(s):  
Risk Assessment ◽  
Traffic Flow ◽  
Assessment Method ◽  
Collision Probability ◽  
Traffic Density ◽  
Automatic Identification ◽  
High Concentration ◽  
Marine Traffic ◽  
Cross Traffic ◽  
Strait Of Malacca

The Strait of Malacca is one of the most important shipping lanes in the world. It averages 150 ship passes a day and more than 50,000 ships annually. With a high concentration of vessels in a narrow path, multiple risk situations arise. Analyzing traffic density is made harder by cross traffic and an unknown traffic density at the Strait. In 2009, Universiti Teknologi Malaysia (UTM), through a collaboration with Kobe University, successfully installed an Automatic Identification System (AIS) receiver. Through the AIS receiver, data of ship movements in the Strait of Malacca and Singapore could be recorded. A program was established by UTM to retrieve the data for the purpose of marine traffic collision risk analysis. In this research, a risk assessment method using AIS data is proposed for restricted waters such as for the Strait of Malacca and Singapore. The Risk Assessment Methodology requires the estimation of collision probabilities. The collision probability of the proposed method considers the Traffic Density, directions of traffic flow (with respect to a subject vessel), and probability of navigational failure. An area in the Strait of Singapore between the latitudes of 1°13’N and 1°07’N and Longitudes of 103°4’E and 103°56’E was selected to illustrate the method. By analysing the AIS data of traffic flow, the probabilities of collision for the area were determined. The effect of vessel parameters of length and speed on the risks of collision are also shown.

scholarly journals Evaluating Strong Currents at a Fairway in the Finnish Archipelago Sea

2018 ◽  
Vol 6 (4) ◽  
pp. 122 ◽  
Author(s):  
Hedi Kanarik ◽  
Laura Tuomi ◽  
Pekka Alenius ◽  
Mikko Lensu ◽  
Elina Miettunen ◽  
...  
Keyword(s):  
Cross Section ◽  
Acoustic Doppler Current Profiler ◽  
Mean Value ◽  
Automatic Identification ◽  
Identification System ◽  
Marine Traffic ◽  
Current Profiler ◽  
System Data ◽  
The Cross ◽  
Oceanographic Conditions

Safe navigation in complex archipelagos requires knowledge and understanding of oceanographic conditions in the fairways. We have studied oceanographic conditions and their relation to weather in a crossing in the Finnish archipelago, which is known to have events when strong currents affect marine traffic. Our main dataset is ADCP (Acoustic Doppler Current Profiler) current measurements, done in the cross section of five months in 2013. We found that the local currents flow mainly to two directions, either to north-northeast (NNE) or to south-southwest (SSW), which is nearly perpendicular to the deepest fairway in the area. The mean value of the currents in the surface layer was 0.087 ms - 1 , but during the high wind situations, the current speed rose over 0.4 ms - 1 . These strong currents were also shown, according to AIS (Automatic Identification System) data, to cause drift of the vessels passing the cross section, though the effect of wind and current to the ship may sometimes be hard to separate. We studied whether the strong currents could be predicted from routine observations of wind and sea level available in the area, and we found that prediction of these currents is possible to some extent. We also found that winds of over 10 ms - 1 blowing from NW (300 ∘ –350 ∘ ) and SE (135 ∘ –180 ∘ ) generated strong currents of over 0.2 ms - 1 , whereas most commonly measured winds from SW (190 ∘ –275 ∘ ) did not generate currents even with winds as high as 15 ms - 1 .

A Model for Calculating a Maritime Risk Criterion Number

1977 ◽  
Vol 30 (2) ◽  
pp. 287-295 ◽  
Author(s):  
C. van der Tak ◽  
J. A. Spaans
Keyword(s):  
Research Centre ◽  
Traffic Density ◽  
Traffic Situation ◽  
Traffic Patterns ◽  
Speed Distribution ◽  
The North ◽  
Marine Traffic ◽  
Risk Criterion ◽  
The North Sea ◽  
Sea Area

Early in 1976 the Navigation Research Centre of the Netherlands Maritime Institute started research to develop a ‘maritime risk criterion number’ for a specific sea area. The need was urgent as the Navigation Research Centre (NRC) became more involved in marine traffic studies in the North Sea and the approaches to Dutch harbours. The main purpose is to calculate the criteria for traffic patterns in a given area as an element in the information needed to find the best regulatory solution for the overall traffic situation. The criterion should give due recognition to such elements as the traffic density, the course and speed distribution of the traffic, and the danger classes of the ships participating in the traffic.

Intelligent Traffic Control System Using Ad-Hoc Wireless sensor Systems

2015 ◽  
Vol 3 (4) ◽  
pp. 333-335
Author(s):  
J. Isaac Henderson ◽  
M. Aravind
Keyword(s):  
Control System ◽  
Traffic Control ◽  
Ad Hoc ◽  
Heavy Traffic ◽  
Wireless Sensor ◽  
Traffic Density ◽  
Data Format ◽  
Infrared Technology ◽  
Traffic Control System ◽  
Signal Time

This paper deals with designing an automatic traffic control  system which works on principle of TRAFFIC DENSITY monitored by  Sensors on each side which provides direct information to microcontroller  which rerforms decision making to allow traffic based on density. The three density zones are low, medium and high. In each zone an ad hoc sensor is placed. Each sensor will check the presence of the vehicle in the zone using infrared technology and then ad hoc sensor sends the data to master ad hoc. To locate the sensor, each sensor of different zone is addressed by user and that address is fed to the master ad hoc sensor. This master ad hoc sensor will arrange the data from various sensors in an 8 bit data format. It then performs the required processing to determine the green signal time for each side. It has an exceptional system for high priority vehicles like ambulance, as it senses the direction of arrival of these vehicles and gives a green corridor. The main advantage over conventional system is that a side with heavy traffic doesn’t have to wait unreasonably while a side with no/less traffic gets an equal  amount of time as that of heavy traffic side which is irascible. This is an improved system based on preference for urgency/density of traffic. This can prove useful in especially Junctions of importance, thereby mediating traffic flow correctly.

scholarly journals Indoor 3D Route Modeling Based On Estate Spatial Data

2014 ◽  
Vol XL-4 ◽  
pp. 357-362 ◽  
Author(s):  
H. Zhang ◽  
Y. Wen ◽  
J. Jiang ◽  
W. Huang
Keyword(s):  
Spatial Data ◽  
Three Dimensional ◽  
Spatial Relationship ◽  
Route Planning ◽  
Weighted Graph ◽  
Emergency Evacuation ◽  
Shopping Mall ◽  
Internal Space ◽  
Existing Building ◽  
Modelling Method

Indoor three-dimensional route model is essential for space intelligence navigation and emergency evacuation. This paper is motivated by the need of constructing indoor route model automatically and as far as possible. By comparing existing building data sources, this paper firstly explained the reason why the estate spatial management data is chosen as the data source. Then, an applicable method of construction three-dimensional route model in a building is introduced by establishing the mapping relationship between geographic entities and their topological expression. This data model is a weighted graph consist of "node" and "path" to express the spatial relationship and topological structure of a building components. The whole process of modelling internal space of a building is addressed by two key steps: (1) each single floor route model is constructed, including path extraction of corridor using Delaunay triangulation algorithm with constrained edge, fusion of room nodes into the path; (2) the single floor route model is connected with stairs and elevators and the multi-floor route model is eventually generated. In order to validate the method in this paper, a shopping mall called "Longjiang New City Plaza" in Nanjing is chosen as a case of study. And the whole building space is constructed according to the modelling method above. By integrating of existing path finding algorithm, the usability of this modelling method is verified, which shows the indoor three-dimensional route modelling method based on estate spatial data in this paper can support indoor route planning and evacuation route design very well.

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