This paper presents a viable approach for incorporating collision avoidance strategies into existing guidance and control systems on marine vessels. We propose a method that facilitates the use of simulation-based Model Predictive Control (MPC) for collision avoidance (COLAV) on marine vessels. Any COLAV strategy to be applied in real traffic must adhere to the international regulations for preventing collisions at sea (COLREGS). The proposed MPC COLAV method does not rely on an accurate model of the guidance system to achieve vessel behaviors that are compliant with the COLREGS. Rather, it depends on transitional costs in the MPC objective for collision avoidance maneuvers that are being executed by the marine vessel. Hence, it is straightforward to implement the MPC COLAV on different vessels without specific knowledge of the vessel's guidance strategy. Moreover, it offers the possibility to switch between different (possibly application specific) guidance strategies on the same vessel while running the same MPC COLAV algorithm. We present results from full scale experiments that show the viability of our method in different collision avoidance scenarios.

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This article presents a new algorithm for short-term maritime collision avoidance (COLAV) named the branching-course model predictive control (BC-MPC) algorithm. The algorithm is designed to be robust with respect to noise on obstacle estimates, which is a significant source of disturbance when using exteroceptive sensors such as, for example, radars for obstacle detection and tracking. Exteroceptive sensors do not require vesselto-vessel communication, which enables COLAV toward vessels not equipped with, for example, automatic identification system transponders, in addition to increasing the robustness with respect to faulty information which may be provided by other vessels. The BC-MPC algorithm is compliant with Rules 8, 13, and 17 of the International Regulations for Preventing Collisions at Sea (COLREGs), and favors maneuvers following Rules 14 and 15. Specifically, the algorithm can ignore the specific maneuvering regulations of Rules 14 and 15, which may be required in situations where Rule 17 revokes a stand-on obligation. The algorithm is experimentally validated in several fullscale experiments in the Trondheimsfjord in 2017 using a radar-based system for obstacle detection and tracking. To complement the experimental results, we present simulations where the BC-MPC algorithm is tested in more complex scenarios involving multiple obstacles and several simultaneously active COLREGs rules. The COLAV experiments and simulations show good performance. K E Y W O R D S control, marine robotics, planning

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We present results from sea trials for an autonomous surface vehicle (ASV) equipped with a collision avoidance system based on model predictive control (MPC). The sea trials were performed in the North Sea as part of an ASV Challenge posed by Deltares through a Dutch initiative involving different authorities, including the Ministry of Infrastructure and Water Management, the Netherlands Coastguard, and the Royal Netherlands Navy. To allow an ASV to operate in a maritime environment governed by the International Regulations for Preventing Collisions at Sea (COLREGs), the ASV must be capable of complying with COLREGs. Therefore, the sea trials focused on verifying COLREGs‐compliant behavior of the ASV in different challenging scenarios using automatic identification system (AIS) data from other vessels. The scenarios cover situations where some obstacle vessels obey COLREGs and emergency situations where some obstacles make decisions that increase the risk of collision. The MPC‐based collision avoidance method evaluates a combined predicted collision and COLREGs‐compliance risk associated with each obstacle and chooses the ‘best’ way out of dangerous situations. The results from the verification exercise in the North Sea show that the MPC approach is capable of finding safe solutions in challenging situations, and in most cases demonstrates behaviors that are close to the expectations of an experienced mariner. According to Deltares’ report, the sea trials have shown in practice that the technical maturity of autonomous vessels is already more than expected.