Analyzing the reliability of autonomous ships has recently attracted attention mainly due to epistemic uncertainty (lack of knowledge) integrated with automatic operations in the maritime sector. The advent of new random failures with unrecognized failure patterns in autonomous ship operations requires a comprehensive reliability assessment specifically aiming at estimating the time in which the ship can be trusted to be left unattended. While the reliability concept is touched upon well through the literature, the operational trustworthiness needs more elaboration to be established for system safety, especially within the maritime sector. Accordingly, in this paper, a probabilistic approach has been established to estimate the trusted operational time of the ship machinery system through different autonomy degrees. The uncertainty associated with ship operation has been quantified using Markov Chain Monte-Carlo simulation from likelihood function in Bayesian inference. To verify the developed framework, a practical example of a machinery plant used in typical short sea merchant ships is taken into account. This study can be exploited by asset managers to estimate the time in which the ship can be left unattended. Keywords: reliability estimation, Bayesian inference, autonomous ship, uncertainty.

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The lack of situational awareness is a major cause of ship collisions. Thus, enhancing the situational awareness of the stand-on ship is a key for navigational safety, where the intention estimation of the give-way ship is crucial. According to COLREGs, the stand-on ship is not allowed to take evasive actions until the give-way ship does not take proper actions timely. The stage that needs the stand-on ship to take actions plays as the second protective layer for the ship, which is named as ‘Stand-on Ship as Second Line of Defense’ (SLoD). A method to estimate the intention of the give-way ship and to trigger SLoD is proposed in this article. Four modules of the proposed method include: “data pre-processing” collects all traffic information and determines the ships' obligations; “action identification” pinpoints the turning points; “action uncertainty” generates a bounded reachable velocity considering the give-way ship's maneuverability; “conflict assessment” judges potential collision by using non-linear velocity obstacle algorithm. Several typical encounter scenarios are simulated to demonstrate the feasibility of the proposed method. The results show that intention estimation of the give-way ship improves the situational awareness of the stand-on ship, which can support the stand-on ship to make collision avoidance decisions.

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Autonomous vessels have become a topic of high interest for the maritime transport industry. Recent progress in the development of technologies enabling autonomous systems has fostered the idea that autonomous vessels will soon be a reality. However, before the first autonomous vessel can be released into her actual context of operation, it is necessary to ensure that it is safe. This is a major challenge as the experience of autonomous ships is very limited. This study highlights the need for elaborating a systemic and systematic hazard analysis since the earliest design phase of an autonomous vessel. In particular, it proposes a process for elaborating an initial hazard analysis and management that provides coherent, transparent and traceable safety input information for the design of an autonomous vessel. The process is applied to analyse the hazards of two autonomous vessel concepts for urban transport in the city of Turku, Finland.

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The growing interest for Arctic and Antarctic shipping activities due to the decreasing ice cover will also increase the risks of accidents on these waters. The design of ships for ice has traditionally been based on the practical experience without a clear link to the physics of the ship-ice interaction. The rules are, however, getting more towards the goal based approach, which require good knowledge of all the various element important for design. Risk based ship design (RBSD) is also widely applied e.g. for the passengers ships. Therefore, the scope of this paper is the review of the knowledge necessary for RBSD for Arctic conditions. The main focus is on ice loads and ship structures. Accident prevention and environmental consequences of oil spills are also discussed, but more briefly. In risk analysis, there is a recent focus on the treatment of uncertainty, or conversely, the strength of knowledge underlying the risk quantification. In light of this, the review is performed with specific focus on the strength of evidence of the different fields of knowledge needed to perform RBSD in ice conditions. The results indicate that the risk based design for Arctic operations is challenging as the ice environment, together with all the possible ship-ice contact scenarios, are complicated to define properly, especially on proper probabilistic terms. The main challenges are still related how to describe the ship-ice interaction parameters such as ship-ice contact characteristics, pressure distributions, and load levels in all the various ice conditions. In addition, the possible environmental consequences of the accidents need further research. Finally, human factors need to be incorporated in risk analysis techniques.@en