AI Solutions for Enhancing Ship Navigation and Collision Avoidance

Sangwoo Jeon, Jueying Li, Hemawathi Somasundaram, Sufyan Yakubu, Sravani Parvathareddy

Abstract


AI solutions are playing a critical role in enhancing ship navigation and collision avoidance, contributing to safer and more efficient maritime operations. This paper explores the methodologies and technologies employed in AI-driven navigation systems, focusing on their applications in real-time situational awareness, route optimization, and hazard detection. By presenting case studies, the paper highlights the benefits of AI solutions, including improved safety, reduced operational costs, and enhanced decision-making. Additionally, the challenges of implementing AI technologies in maritime navigation are discussed, along with future prospects for their integration into ship operations.

Keywords


AI, ship navigation, collision avoidance, maritime safety.

References


Akdağ, Melih, et al. “Collaborative Collision Avoidance for Maritime Autonomous Surface Ships: A Review”. Ocean Engineering, vol. 250, Elsevier, 2022, p. 110920.

Burmeister, Hans-Christoph, and Manfred Constapel. “Autonomous Collision Avoidance at Sea: A Survey”. Frontiers in Robotics and AI, vol. 8, Frontiers Media SA, 2021, p. 739013.

Campbell, Sable, et al. “A Review on Improving the Autonomy of Unmanned Surface Vehicles through Intelligent Collision Avoidance Manoeuvres”. Annual Reviews in Control, vol. 36, no. 2, Elsevier, 2012, pp. 267–283.

Chen, Chen, et al. “A Novel Ship Collision Avoidance Awareness Approach for Cooperating Ships Using Multi-Agent Deep Reinforcement Learning”. Journal of Marine Science and Engineering, vol. 9, no. 10, Multidisciplinary Digital Publishing Institute, 2021, p. 1056.

Chun, Do-Hyun, et al. “Deep Reinforcement Learning-Based Collision Avoidance for an Autonomous Ship”. Ocean Engineering, vol. 234, Elsevier, 2021, p. 109216.

Huang, Yamin, et al. “Ship Collision Avoidance Methods: State-of-the-Art”. Safety Science, vol. 121, Elsevier, 2020, pp. 451–473.

Li, Lingyu, et al. “A Path Planning Strategy Unified with a COLREGS Collision Avoidance Function Based on Deep Reinforcement Learning and Artificial Potential Field”. Applied Ocean Research, vol. 113, Elsevier, 2021, p. 102759.

Perera, L. P., et al. “Fuzzy Logic Based Decision Making System for Collision Avoidance of Ocean Navigation under Critical Collision Conditions”. Journal of Marine Science and Technology, vol. 16, Springer, 2011, pp. 84–99.

Perera, Lokukaluge P. “Autonomous Ship Navigation under Deep Learning and the Challenges in COLREGs”. International Conference on Offshore Mechanics and Arctic Engineering, vol. 51333, American Society of Mechanical Engineers, 2018, p. V11BT12A005.

Perera, Lokukaluge P. “Deep Learning toward Autonomous Ship Navigation and Possible COLREGs Failures”. Journal of Offshore Mechanics and Arctic Engineering, vol. 142, no. 3, American Society of Mechanical Engineers, 2020, p. 031102.

Statheros, Thomas, et al. “Autonomous Ship Collision Avoidance Navigation Concepts, Technologies and Techniques”. The Journal of Navigation, vol. 61, no. 1, Cambridge University Press, 2008, pp. 129–142.

Tam, Cheekuang, et al. “Review of Collision Avoidance and Path Planning Methods for Ships in Close Range Encounters”. The Journal of Navigation, vol. 62, no. 3, Cambridge University Press, 2009, pp. 455–476.

Thombre, Sarang, et al. “Sensors and AI Techniques for Situational Awareness in Autonomous Ships: A Review”. IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 1, IEEE, 2020, pp. 64–83.

Tsou, Ming-Cheng, and Chao-Kuang Hsueh. “The Study of Ship Collision Avoidance Route Planning by Ant Colony Algorithm”. Journal of Marine Science and Technology, vol. 18, no. 5, 2010, p. 16.

Tsou, Ming-Cheng, et al. “Decision Support from Genetic Algorithms for Ship Collision Avoidance Route Planning and Alerts”. The Journal of Navigation, vol. 63, no. 1, Cambridge University Press, 2010, pp. 167–182.

Zaccone, Raphael, and Michele Martelli. “A Collision Avoidance Algorithm for Ship Guidance Applications”. Journal of Marine Engineering & Technology, vol. 19, no. sup1, Taylor & Francis, 2020, pp. 62–75.

Zhang, Jinfen, et al. “An Interpretable Knowledge-Based Decision Support Method for Ship Collision Avoidance Using AIS Data”. Reliability Engineering & System Safety, vol. 230, Elsevier, 2023, p. 108919.

Zhang, Xinyu, et al. “Collision-Avoidance Navigation Systems for Maritime Autonomous Surface Ships: A State of the Art Survey”. Ocean Engineering, vol. 235, Elsevier, 2021, p. 109380.


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