An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels

This study presents a method to predict the future trajectory of a target vessel using historical AIS data. The purpose of such a prediction is to aid in collision avoidance in future vessels. The method presented in this study extracts all trajectories present in an initial cluster centered about a...

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Bibliographic Details
Published in:Volume 7B: Ocean Engineering
Main Authors: Murray, Brian, Perera, Lokukaluge Prasad
Format: Book Part
Language:English
Published: American Society of Mechanical Engineers (ASME) 2019
Subjects:
VDP::Technology: 500::Marine technology: 580::Offshore technology: 581
VDP::Teknologi: 500::Marin teknologi: 580::Offshoreteknologi: 581
Arctic
Online Access:https://hdl.handle.net/10037/18359
https://doi.org/10.1115/OMAE2019-95963
Description
Summary:This study presents a method to predict the future trajectory of a target vessel using historical AIS data. The purpose of such a prediction is to aid in collision avoidance in future vessels. The method presented in this study extracts all trajectories present in an initial cluster centered about a vessel position. Features for each trajectory are then generated using Principle Component Analysis and used in clustering via unsupervised Gaussian mixture modeling. Each resultant cluster represents a possible future route the vessel may follow. A trajectory prediction is then conducted with respect to each cluster of trajectories discovered. This results in a prediction of multiple possible trajectories. The results indicate that the algorithm is effective in clustering the trajectories, where at least one cluster corresponds to the true trajectory of the vessel. The resultant predicted trajectories are also found to be reasonably accurate.

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