Framework of an Evolutionary Multi-Objective Optimisation Method for Planning a Safe Trajectory for a Marine Autonomous Surface Ship

Abstract

This paper represents the first stage of research into a multi-objective method of planning safe trajectories for marine autonomous surface ships (MASSs) involved in encounter situations. Our method applies an evolutionary multi-objective optimisation (EMO) approach to pursue three objectives: minimisation of the risk of collision, minimisation of fuel consumption due to collision avoidance manoeuvres, and minimisation of the extra time spent on collision avoidance manoeuvres. Until now, a fully multi-objective optimisation has not been applied to the real-time problem of planning safe trajectories; instead, this optimisation problem has usually been reduced to a single aggregated cost function covering all objectives. The aim is to develop a method of planning safe trajectories for MASSs that is able to simultaneously pursue the three abovementioned objectives, make decisions in real time and without interaction with a human operator, handle basic types of encounters (in open or restricted waters, and in good or restricted visibility) and guarantee compliance with the International Regulations for Preventing Collisions at Sea. It should also be mentioned that optimisation of the system based on each criterion may occur at the cost of the others, so a reasonable balance is applied here by means of a configurable trade-off. This is done throughout the EMO process by means of modified Pareto dominance rules and by using a multi-criteria decision-making phase to filter the output Pareto set and choose the final solution

Autonomous ships and the collision avoidance regulations: a licensed deck officer survey

“…Amendments were preferred in five of the rules: rules 2a, 3a, 10b, 19e, and 23a. This is in line with Hirst (2020), Komianos (2018), and Szłapczyński and Ghaemi (2019), who state that MASS cannot comply with the COLREGs as written and they should be amended. The amendment in rule 2a adds that the responsibility of the ordinary practice of seamen is transferable to the responsible party ashore.…”

Control of Dynamic Positioning System with Disturbance Observer for Autonomous Marine Surface Vessels

“…Extensive development work is currently underway on the concept of the Maritime Autonomous Surface Ship (MASS), which requires new solutions in many areas: law, economics, guidance, control and navigation [1][2][3]. Automated navigation tasks require the further development of high-level control systems; in particular, with respect to such issues as path planning and collision avoidance [4][5][6][7][8][9][10][11][12][13][14][15]. However, the basic issue in the research on developing autonomous marine surface vessels is motion control.…”

Artificial Intelligence-Based Methods for Decision Support to Avoid Collisions at Sea

“…On the other hand, many techniques have been proposed for solving the aforementioned problem of ship steering in specific cases, based on both conventional techniques and more developed ones. Herein, the main aim was to provide assistance to navigators in terms of making the appropriate and accurate maneuvering decisions under certain conditions, using such techniques as those proposed in the references [18][19][20][21][22][23][24][25]. The study presented in this paper was dedicated to the issue of determining the optimal safe trajectory of a ship at sea, where many other ships can be encountered in the vicinity, using selected methods based on artificial intelligence techniques, such as fuzzy logic, neural network, genetic algorithms, and particle swarm optimization algorithms.…”