Development of recommendations for digital testing of MASS navigation safety prior to sea trials

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Chua, Kie Hian and Coutinho, Savio and Norahim, Aizad and Konovessis, Dimitrios (2022) Development of recommendations for digital testing of MASS navigation safety prior to sea trials. Journal of Physics: Conference Series, 2311 (1). 012025. ISSN 1742-6588 (https://doi.org/10.1088/1742-6596/2311/1/012025)

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Abstract

For Maritime Autonomous Surface Ships (MASS), a key area that has seen active development is in the use of autonomous capabilities for vessel navigation and control. This can range from a simple use case of waypoint navigation, which takes into account bathymetry and navigation markers, to complex collision avoidance scenarios where the autonomous systems are required to detect, evaluate and execute evasive manoeuvres based on time and spatially varying dynamic behaviour of other vessels. In Singapore, it has been identified that there is a need to carry out accurate digital testing of MASS navigation safety before sea trials. This is where a vessel developer is required to demonstrate that the MASS is able to carry out the sea trials safely, and to stress test high risk scenarios that may not be practicably tested in the sea trials. A study has been carried out to develop recommendations for the digital testing, which takes into consideration the need for accurate representation of the actual MASS being built, as well as the verification of the autonomous navigation algorithm’s capabilities to safely control the vessel in real-world scenarios. Based on the study, a three-stage framework is proposed. Firstly, the accuracy of the digital model in representing the dynamic responses of the actual vessel is verified and any discrepancy with benchmark data is to be quantified. Secondly, tests are carried out to ascertain that the autonomous navigation algorithm is able to control (virtually) the dynamically-accurate vessel from one point to another, taking into account the real-world environmental loads. Lastly, the ability of the autonomous navigation algorithm in carrying out collision detection and avoidance is verified. As part of the study, a review of the current state-of-art and engagement with the industry has been carried out. These details are described in this paper.

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