The Autonomous Navigation System (ANS) constitutes a critical key enabling technology required for operating Maritime Autonomous Surface Ships (MASS). To assure the safety of MASS operations, the effective identification of potential objects and target ships interacting with the own MASS is quintessential. This study proposes a systematic method to identify the items interacting with the own MASS. This method is based on a similar approach previously employed for the encountering items’ identification in robotics, which is customised herein for the MASS needs. The developed method is applied to a short-sea shipping MASS. The environmental features, agents and objects related to her navigation are identified and ranked based on the frequency of encounter and the potential collision consequences. The results demonstrate the ability of the method to identify additional items in comparison to Automatic Identification System based data. The interactions with the small ships are considered as the most critical, due to their potential accidental consequences and their exhibited high frequency of encounter. This study results are employed to support the ANS design and testing of the investigated ship.

According to the mid-term review of the EU White Paper on Transport, short sea shipping is expected to grow at a rate of 59% in metric tonnes, from 2000 to 2020. If we consider that the overall expected growth in freight exchanges is of some 50%, sea transport is one of the most feasible ways to reduce traffic congestion on European roads. High speed vessels are a possible way to compete with road transport on certain routes; however, these ships are highly affected by heavy weather. This paper analyses the weather influence on several short sea shipping routes to be served by fast ships.