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.

Automatic Identification System Receiver for Small Fishing Vessels

2020 ◽  
Author(s):  
Febus Reidj G. Cruz ◽  
Jeremiah A. Ordiales ◽  
Malvin Angelo C. Reyes ◽  
Pinky T. Salvanera
Keyword(s):  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Fishing Vessels

Automatic identification system data-driven model for analysis of ship domain near bridge-waters

2021 ◽  
pp. 1-22
Author(s):  
Lei Jinyu ◽  
Liu Lei ◽  
Chu Xiumin ◽  
He Wei ◽  
Liu Xinglong ◽  
...  
Keyword(s):  
Least Squares Method ◽  
Automatic Identification ◽  
Identification System ◽  
Collision Risk ◽  
Automatic Identification System ◽  
Domain Models ◽  
System Data ◽  
Quantification Model ◽  
Highly Correlated

Abstract The ship safety domain plays a significant role in collision risk assessment. However, few studies take the practical considerations of implementing this method in the vicinity of bridge-waters into account. Therefore, historical automatic identification system data is utilised to construct and analyse ship domains considering ship–ship and ship–bridge collisions. A method for determining the closest boundary is proposed, and the boundary of the ship domain is fitted by the least squares method. The ship domains near bridge-waters are constructed as ellipse models, the characteristics of which are discussed. Novel fuzzy quaternion ship domain models are established respectively for inland ships and bridge piers, which would assist in the construction of a risk quantification model and the calculation of a grid ship collision index. A case study is carried out on the multi-bridge waterway of the Yangtze River in Wuhan, China. The results show that the size of the ship domain is highly correlated with the ship's speed and length, and analysis of collision risk can reflect the real situation near bridge-waters, which is helpful to demonstrate the application of the ship domain in quantifying the collision risk and to characterise the collision risk distribution near bridge-waters.

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