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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American Society of Mechanical Engineers (ASME)
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Online Access: | https://hdl.handle.net/10037/18359 https://doi.org/10.1115/OMAE2019-95963 |
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ftunivtroemsoe:oai:munin.uit.no:10037/18359 2023-05-15T14:26:22+02:00 An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels Murray, Brian Perera, Lokukaluge Prasad 2019-11-11 https://hdl.handle.net/10037/18359 https://doi.org/10.1115/OMAE2019-95963 eng eng American Society of Mechanical Engineers (ASME) Murray, B.; Perera, L.P. (2019) An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels In: Proceedings of ASME 2019 ,8th International Conference on Ocean, Offshore and Arctic Engineering, vol. 7B: Ocean Engineering, . https://doi.org/10.1115/OMAE2019-95963 FRIDAID 1748254 doi:10.1115/OMAE2019-95963 978-0-7918-5885-1 1523-651X https://hdl.handle.net/10037/18359 openAccess Copyright © 2019 by ASME VDP::Technology: 500::Marine technology: 580::Offshore technology: 581 VDP::Teknologi: 500::Marin teknologi: 580::Offshoreteknologi: 581 Peer reviewed Bok Chapter publishedVersion 2019 ftunivtroemsoe https://doi.org/10.1115/OMAE2019-95963 2021-06-25T17:57:22Z 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. Book Part Arctic University of Tromsø: Munin Open Research Archive Volume 7B: Ocean Engineering |
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University of Tromsø: Munin Open Research Archive |
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ftunivtroemsoe |
language |
English |
topic |
VDP::Technology: 500::Marine technology: 580::Offshore technology: 581 VDP::Teknologi: 500::Marin teknologi: 580::Offshoreteknologi: 581 |
spellingShingle |
VDP::Technology: 500::Marine technology: 580::Offshore technology: 581 VDP::Teknologi: 500::Marin teknologi: 580::Offshoreteknologi: 581 Murray, Brian Perera, Lokukaluge Prasad An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels |
topic_facet |
VDP::Technology: 500::Marine technology: 580::Offshore technology: 581 VDP::Teknologi: 500::Marin teknologi: 580::Offshoreteknologi: 581 |
description |
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. |
format |
Book Part |
author |
Murray, Brian Perera, Lokukaluge Prasad |
author_facet |
Murray, Brian Perera, Lokukaluge Prasad |
author_sort |
Murray, Brian |
title |
An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels |
title_short |
An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels |
title_full |
An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels |
title_fullStr |
An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels |
title_full_unstemmed |
An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels |
title_sort |
ais-based multiple trajectory prediction approach for collision avoidance in future vessels |
publisher |
American Society of Mechanical Engineers (ASME) |
publishDate |
2019 |
url |
https://hdl.handle.net/10037/18359 https://doi.org/10.1115/OMAE2019-95963 |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
Murray, B.; Perera, L.P. (2019) An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels In: Proceedings of ASME 2019 ,8th International Conference on Ocean, Offshore and Arctic Engineering, vol. 7B: Ocean Engineering, . https://doi.org/10.1115/OMAE2019-95963 FRIDAID 1748254 doi:10.1115/OMAE2019-95963 978-0-7918-5885-1 1523-651X https://hdl.handle.net/10037/18359 |
op_rights |
openAccess Copyright © 2019 by ASME |
op_doi |
https://doi.org/10.1115/OMAE2019-95963 |
container_title |
Volume 7B: Ocean Engineering |
_version_ |
1766298894904328192 |