Projects per year
Abstract
The maritime industry has been progressing towards autonomous shipping with the main barrier and scepticism eing on the safety assurance of the next-generation autonomous ships. This study aims to enhance the safety of the autonomous ships by developing an intelligent agent that makes evasive decisions considering the ship domain as a safety zone. The proposed approach is demonstrated by considering the case study of a short sea shipping cargo ship. An intelligent reinforcement learning agent is trained to maoneuvre the investigated ship in restricted sea area. The results of this study verify the agent's ability to make safe evasive decisions and control the autonomous collision avoidance for autonomous ships in known and unknown environments.
| Original language | English |
|---|---|
| Number of pages | 6 |
| Publication status | Published - 7 Apr 2022 |
| Event | The 4th International Conference on Maritime Autonomous Surface Ships (ICMASS) and The International Maritime and Port Technology and Development Conference - Singapore, Singapore Duration: 6 Apr 2022 → 7 Apr 2022 https://nfas.autonomous-ship.org/arrangement/mtec-icmass-2022/ |
Conference
| Conference | The 4th International Conference on Maritime Autonomous Surface Ships (ICMASS) and The International Maritime and Port Technology and Development Conference |
|---|---|
| Abbreviated title | ICMASS/MTEC |
| Country/Territory | Singapore |
| City | Singapore |
| Period | 6/04/22 → 7/04/22 |
| Internet address |
Funding
The authors greatly acknowledge the funding from DNV AS and RCCL for the Maritime Safety Research Centre (MSRC) establishment and operation. The opinions expressed herein are those of the authors and should not be construed to reflect the views of DNV AS and RCCL. Part of this study was carried out in the framework of the AUTOSHIP project, which is funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 815012.
Keywords
- maritime autonomous surface ships (MASS)
- autonomous collision avoidance system
- decision-making
- risk metrics
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Dive into the research topics of 'Autonomous collision avoidance control using deep reinforcement learning for maritime autonomous surface ships'. Together they form a unique fingerprint.Projects
- 1 Finished
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Autonomous Shipping Initiative for European Waters (AUTOSHIP)
Theotokatos, G. (Principal Investigator), Boulougouris, E. (Co-investigator) & Vassalos, D. (Co-investigator)
European Commission - Horizon Europe + H2020
1/06/19 → 30/11/23
Project: Research