In a significant stride for the maritime industry, a comprehensive review of ship manoeuvring research from 2010 to 2025 has been published, shedding light on the evolution of this critical field. Led by Mina Tadros from the Department of Naval Architecture, Ocean and Marine Engineering at the University of Strathclyde, the study, published in the ‘Journal of Marine Science and Engineering’ (or ‘Journal of Ocean and Marine Engineering’ in English), traces the journey from traditional hydrodynamic models to advanced, intelligent systems that are set to revolutionise maritime operations.
The review, which draws on a structured bibliometric dataset, highlights how ship manoeuvring has transformed from a niche area of marine hydrodynamics into a multidisciplinary research enabler. This evolution has integrated seakeeping and intact stability, paving the way for digital twins and autonomous maritime systems. Tadros and her team have organised the literature into interconnected themes, including physics-based manoeuvring models, adaptive and predictive control, machine learning, digital-twin technologies, collision-avoidance and regulatory reasoning, environmental performance, and cooperative autonomy.
One of the key findings is the shift from static empirical modelling to hybrid physics and artificial intelligence (AI) frameworks. These advanced systems are capable of capturing nonlinear dynamics, uncertainty, and multi-vessel interactions. “The transition from static empirical modelling toward hybrid physics, artificial intelligence (AI) frameworks capable of capturing nonlinear dynamics, uncertainty, and multi-vessel interactions,” Tadros noted, underscoring the significance of this shift.
The study also highlights the growing influence of regulations such as the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) and the Second-Generation Intact Stability Criteria, as well as emissions-reduction targets, in shaping technical developments. This regulatory framework is driving the development of learning-enabled prediction, model predictive control (MPC)-based regulatory compliance, and real-time digital-twin synchronisation.
For the maritime industry, the implications are profound. The integration of digital twins and AI into ship manoeuvring offers unprecedented opportunities for improving safety, efficiency, and environmental performance. These technologies can support safe, efficient, and regulation-compliant autonomous maritime systems, which are expected to play a central role in the future of shipping.
However, the review also identifies unresolved challenges, including domain shift, model interpretability, certification barriers, multi-agent safety guarantees, and digital-twin divergence under sparse data. Addressing these challenges will be crucial for the widespread adoption of these advanced systems.
In summary, the study by Tadros and her team presents ship manoeuvring as a central pillar of future Maritime Autonomous Surface Ships (MASS) operations and sustainable shipping. By mapping both demonstrated capabilities and conceptual frontiers, the review outlines a research agenda toward integrated, explainable, and environmentally aligned manoeuvring intelligence. This agenda is set to guide the maritime industry towards a future where autonomous systems play a pivotal role in safe and efficient shipping operations.