Enhancing Safety in Autonomous Navigation: Weather-Aware Trajectory Planning

In a context where autonomous navigation aims to enhance safety and comfort, this work introduces an adaptive weather routing algorithm for autonomous ships. Unlike traditional ships, where the final decision on the route is always entrusted to the captain, despite possible support from weather routing algorithms, on autonomous ships, it is necessary to automate the trajectory choice to protect cargo, structure, and, if present, crew engaged in activities, for example, research. The core of the study is the development of an efficient adaptive weather routing model that optimizes the ship's response in adverse marine conditions, implementing two approaches: the Dijkstra algorithm and the genetic algorithm. The comparison between these methods aims to determine which is more effective in adapting to such challenges, with the final goal of ensuring safer, more comfortable journeys with lower risks for cargo and ship.

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Published
2024-10-14
DOI
https://doi.org/10.1109/metrosea62823.2024.10765702
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
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article

Enhancing Safety in Autonomous Navigation: Weather-Aware Trajectory Planning

Silvia Pennino, Egidio D’Amato
Autonomous Vehicle Technology and Safety
article

Enhancing Safety in Autonomous Navigation: Weather-Aware Trajectory Planning

Silvia Pennino, Egidio D’Amato
article en

Abstract

In a context where autonomous navigation aims to enhance safety and comfort, this work introduces an adaptive weather routing algorithm for autonomous ships. Unlike traditional ships, where the final decision on the route is always entrusted to the captain, despite possible support from weather routing algorithms, on autonomous ships, it is necessary to automate the trajectory choice to protect cargo, structure, and, if present, crew engaged in activities, for example, research. The core of the study is the development of an efficient adaptive weather routing model that optimizes the ship's response in adverse marine conditions, implementing two approaches: the Dijkstra algorithm and the genetic algorithm. The comparison between these methods aims to determine which is more effective in adapting to such challenges, with the final goal of ensuring safer, more comfortable journeys with lower risks for cargo and ship.

Parthenope University of Naples (IT)
Climate action
Openalex Percentile: Top 77%
Autonomous Vehicle Technology and Safety
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