In the shipping digitalisation process, the peak will be reached with the advent of a wholly autonomous and at the same time safe and reliable ship. Full autonomy could be obtained by two linked Artificial-Intelligence systems representing the ship navigator and the ship engineer that possess sensing and analysis skills, situational awareness, planning, and control capabilities. Many efforts have been made in developing onboard systems; however, the shore facilities are not ready yet to deal with these new technologies. The paper aims to present the innovative technologies and methodologies needed to develop a futuristic Vessel Traffic System. The proposed systems will aim at faultless data acquisition and processing, provide input to decision-making systems, and suggest evasive manoeuvre; to deal with hazards and systems failure without human intervention onboard. The system is composed of three different and interacting layers. The first is an artificially intelligent tool to detect and control autonomous ships, thanks to situation recognition and obstacle avoidance strategies. The second is an orchestration and management platform designed to coordinate the sensing/actuation infrastructure and the AI algorithms’ results made available by multiple ships, mustering edge, and distributed computing techniques to fulfil the specific harsh requirements of the sea environment. The final part is a holistic guidance-navigation-control framework to manage autonomous ships’ navigation in a crowded area. Eventually, a cyber-physical scenario, using both a ship digital-twin and a real model-scale ship, is suggested to test and validate the innovative system without the availability of a full-scale scenario.

The paper presents a collision avoidance algorithm for ship open sea navigation, based on an ad hoc modified version of the Rapidly-exploring Random Tree (RRT*) algorithm. The proposed approach is designed to act as the high level layer of the navigation control structure for an autonomous ship. Collision and grounding still represent the primary source of sea accidents, thus an automatic system able to detect static and moving obstacles and plan an evasive route could significantly improve safety during navigation, especially in crowded areas. Focusing on the maritime field, a review of the scientific literature dealing with collision avoidance is presented, showing potential benefits and weaknesses of the different approaches. Among the several methods, details about the RRT and RRT* algorithms are given. The ship path planning problem is introduced and discussed, formulating suitable cost functions and taking into account both topological and kinematic constraints. The algorithm is able to manage multiple moving obstacles with variable speed and course. Eventually, a time-domain ship simulator is used to test the effectiveness of the proposed algorithm over a number of realistic operation scenarios. The obtained results are presented and critically discussed.

In recent decades, the design of ship propulsion systems has been focusing on energy efficiency and low pollutant emissions. In this framework, diesel–electric propulsion has become a standard for many ship types and has proven its worth for flexible propulsion design and management. This paper presents an approach to the optimal design of diesel–electric propulsion systems, minimising the fuel consumption while meeting the power and speed requirements. A genetic algorithm performs the optimisation, used to determine the number and type of engines installed on-board and the engines’ design speed and power, selecting within a dataset of four-stroke diesel engines. The same algorithm is then adapted and applied to determine the optimal load sharing strategy in off-design conditions, taking advantage of the high flexibility of the diesel–electric propulsion plants. In order to apply the algorithm, the propulsion layout design is formulated as an optimisation problem, translating the system requirements into a cost function and a set of linear and non-linear constraints. Eventually, the method is applied to a case study vessel: first, the optimal diesel–electric propulsion plants are determined, then the optimal off-design load sharing and working conditions are computed. AC and DC network solutions are compared and critically discussed in both design and off-design conditions.

A turbocharged diesel engine numerical model, suitable for real-time ship manoeuvre simulation, is presented in this paper. While some engine components (mainly the turbocharger, intercooler and manifolds) are modelled by a filling and emptying approach, the cylinder simulation is based on a set of five-dimensional numerical matrices (each matrix is generated by means of a more traditional thermodynamic model based on in-cylinder actual cycle). The new cylinder calculation approach strongly reduces the engine transient computation time, making it possible to transform the simulation model into a real-time executable application. As a case study, the simulation methodology is applied to a high speed four stroke turbocharged marine diesel engine, whose design and off design running data are available from the technical sheet. In order to verify the suitability of the proposed model in real-time simulation applications, a yacht propulsion plant simulator is developed. Numerical results in ship acceleration and deceleration manoeuvres are shown, reducing the simulation running time of 99% in comparison with the corresponding in-cylinder actual cycle engine model.