This paper presents a multiobjective optimisation approach for path planning of autonomous surface vehicles (ASVs). A unique feature of the technique is the unification of the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) with good seamanship's practice alongwith hierarchical (rather than simultaneous) inclusion of objectives. The requirements of collision avoidance are formulated as mathematical inequalities and constraints in the optimisation framework and thus collision-free manoeuvres and COLREGs-compliant behaviours are provided in a seafarerlike way. Specific expert knowledge is also taken into account when designing the multiobjective optimisation algorithm. For example, good seamanship reveals that if allowed, an evasive manoeuvre with course changes is always preferred over one with speed changes in practical maritime navigation. As a result, a hierarchical sorting rule is designed to prioritize the objective of course/speed change preference over other objectives such as path length and path smoothness, and then incorporated into a specific evolutionary algorithm called hierarchical multiobjective particle swarm optimisation (H-MOPSO) algorithm. The H-MOPSO algorithm solves the real-time path planning problem through finding solutions of the formulated optimisation problem. The effectiveness of the proposed H-MOPSO algorithm is demonstrated through both desktop and high-fidelity networked bridge simulations.

In this paper, a multiobjective optimization framework is proposed for on-line path planning of autonomous surface vehicles (ASVs), where both collision avoidance and COLREGscompliance are taken into account. Special attention has been paid to situational awareness and risk assessment, particularly when the target ship is in breach of the COLREGs rules defined by the International Maritime Organisation. In order to implement COLREGs, the rules together with physical constraints are formulated as mathematical inequalities. A multiobjective optimization problem based on particle swarm optimization is then solved, the solution of which represents a newly-generated path. It is shown through simulations that the proposed method is able to generate COLREGs-compliant and collision-free paths even for non-cooperative targets i.e. vessels that are in breach of COLREGs.

In this paper, we explore the learning and teaching of a maritime simulation programme to understand its deep learning elements. We followed the mixed methods approach and collected student perception data from a maritime school, situated within a UK university, using reflection-based survey (n = 112) and three focus groups with eleven students. Findings include the needs for defining clear learning outcomes, improving the learning content to enable exploration and second-chance learning, minimising theory–practice gaps by ensuring skills-knowledge balance and in-depth scholarship building, facilitating tasks for learning preparation and learning extension, and repositioning simulation components and their assessment schemes across the academic programme. Overall, the paper provides evidence on the importance of deep learning activities in maritime simulation and suggests guidelines on improving the existing practice. Although the findings are derived from a maritime education programme, they can be considered and applied in other academic disciplines which use simulation in their teaching and learning.

Simulations and games are being used across a variety of subject areas as a means to provide insight into real world situations within a classroom setting; they offer many of the benefits of real world learning but without some of the associated risks and costs. Lean, Moizer, Derham, Strachan and Bhuiyan aim to evaluate the role of simulations and games in real world learning. The nature of simulations and games is discussed with reference to a variety of examples in Higher Education. Their role in real world learning is evaluated with reference to the benefits and challenges of their use for teaching and learning in Higher Education. Three case studies from diverse subject contexts are reported to illustrate the use of simulations and games and some of the associated issues.

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