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The presence of autonomous vehicles in the maritime domain is already a reality, even though being confined to very specific domains of operations (environmental monitoring, surveillance and defense, R&D) or segregated spaces (exclusive spaces for the operation of autonomous vehicles). Artificial Intelligence algorithms for navigation control applied in autonomous vessels are based on the adoption of rules that currently regulate navigation, namely the International Collision Regulation (ColReg), the maritime Buoyage System, and routing regulations. However, considering Jen Rasmussen's decision model, in many situations, the navigator makes decisions not only based on rules (Rule-Based) but based on perceptions that stem from his skills (Skill Based) or knowledge (Knowledge-Based). An example is the concept of safe speed or safe distance, defined in ColReg, but with a variable quantification depending on the circumstances. On the other hand, the navigator's perception of the concept of navigation safety varies significantly and usually goes beyond the ship domain. For instance, some may decide not complying a ColReg priority rule to facilitate another vessel's movement and prevent a decrease in the operation safety level. Safety perception is conceived holistically, that is, it is not restricted to the vessel, but to all those in the vicinity and the natural environment. Finally, it is important to understand the behaviour of navigators in the face of the existence or interaction with unmanned vessels, not only to understand how the decision process is affected but also to improve the AI algorithms applied in autonomous vehicles.To understand how the perceived status of the encountered vessels affects the navigator's decision, we conducted an experimental study to assess how the decisions made by the participant vary when interacting with unmanned vessels. Recognizing that trust in automation is a critical influential factor, we adopted existing framework models to evaluate the participants' perceptions of Maritime Autonomous Surface Ships (MASS), as classified by the International Maritime Organization.The adopted method comprises a combination of questionnaires and participation in six simulated scenarios. This mixed approach aimed to understand the familiarity with MASS; the need to change operational regulations; concerns, challenges, and opportunities from the implementation of MASS; trust in MASS; and the differences between the declared perception and decision-making when interacting with MASS.The study comprised three stages. firstly, a pilot study to appraise and validate the questionnaire, with 49 participants. Secondly, the online implementation of the questionnaire, with a desktop version of the six simulated scenarios, with 110 valid questionnaires, 73 students from the naval academy and 37 professional mariners. Each scenario presented an interaction situation with another vessel, referencing a clearly stated rule of the Collision Regulation. The target vessel could randomly assume one of three statuses: Manned vessel, Unmanned vessel and unidentified vessel. By varying the control mode of the target vessel in the same situation, we aimed to see if the perceived status of the vessel had any influence on the decision-making process. In the last stage of the study, the six desktop exercises of the scenarios were replaced by a simulator game of the same situation, with 33 participants. On the desktop exercise participants reported: Time for acting, change of heading, change of speed, and aimed final position. Reaction time, change of heading and speed were automatically logged on the simulator game. The questionnaire comprises four sections: Unmanned vessels and levels of automation, scenarios decisions, trust in automation and demographic data.The results suggest that despite having a reduced familiarity with autonomous ships, the participants have a very positive opinion. However, in the same situation, they react differently to conventional ships and autonomous ships. The way navigators react was analyzed through parameters such as reaction time, course and speed variation and the Closest Point of Approach between vessels. There is a greater discrepancy between those parameters in participants with less training, suggesting a need to address the issues of interaction with unmanned vessels during the course program. Results from the simulators provided more precise shreds of evidence, namely when interacting with unidentified vessels, pointing out the need to design solutions for clear identification of the target vessel.

Maritime navigation is a demanding and complex domain that involves risks for people, the environment, and economic activity. The tasks associated with its execution require advanced training, expertise, experience, and a collaborative Navigation Team. Furthermore, naval operations demand higher readiness, accuracy, and resilience due to additional constraints. The response to these challenges has been integrating further automation and information systems. However, the effectiveness of innovative trends had been questioned by recent naval accidents like those involving the US and Norwegian naval ships.In bridge crews, collaboration is progressively more dependent on technological means since they are the information sources, and team members need to share and exchange different information formats besides audio. Furthermore, the increasing number of control functions and information systems required to strengthen the bridge situational awareness came with an additional cost to human operators. Therefore, navigation teams need further assistance in this challenging context to achieve a consistent and coherent situational awareness regarding the integrated systems in use, comprising technological and human agents' activities. The proposed solution under development is a Collaborative Decision Support System (C-DSS) fitted to the vessels' bridge systems requirements to reduce the cognitive workload, enhance collaboration between team members and information systems, and strengthen team situational awareness and sensemaking.Several studies addressed the need to provide enhanced interfaces with higher levels of abstraction representation, adjusted to the changed role of human operators, easily adaptable; improved collaboration between humans and automated agents, and superior information integration from internal and external environments. The most critical property of interfaces is to simplify the "discovery of the meaningfulness" of the problem space. World's representation should include the relevant and critical elements tailored to the task, augmenting the interaction experience, increasing the decision-making skill, and assisting the discovery of significant phenomena. The used methodology was an anthropocentric approach to innovation - design thinking. The process was performed with five phases: empathy, definition, idealization, prototyping and tests. Interface design prototypes were made with Mockups, covering the following several team roles. Usability tests, questionnaires and interviews were applied to validate and assess the C-DSS. Five focus group tests were made iteratively, with fifteen SMEs, twice with navigators, and once with SMEs from the other role, three in each iterative evaluation test, with a 1.5-hour duration. Following a snowball selection principle, participants were recruited from the Portuguese navy with the organization's guidance to ensure that all participants had an extensive seagoing experience.At the current stage of the C-DSS development, the results indicate significant potential for interface strategies. Results show that end-users would like to have the C-DSS, considering it innovative, friendly, easy to learn and with the information they need. The usability test allowed us to correct and improve numerous user interface design issues. The main difficulties maintained in terms of usability were related to recording data. The envisaged C-DSS is fitted to the vessels' bridge systems requirements embracing several prerequisites like being portable and customizable, enabling goals and priorities' management, logging performance and behavioural data, sharing different information formats, supporting information synchronization, providing situational awareness information about the system and operators.This study contributes to the understanding of the collaborative decision-making process in navigation teams through two objectives: first, systematising the main difficulties and challenges and, second, presenting a desirable solution, possible from a technological and financially viable point of view. The developed prototype has four distinct graphic interfaces, that complement each other and are oriented to the context of the user's role, based on the continuous contribution of target users, that is, elements belonging to navigation teams. The contributions allowed an improved understanding of the problem, idealise the solution, and improve the C-DSS, from design to insertion and adaptation of new functions.In the validation process of the prototype, it was found that the experts would like to use the C-DSS, stating that they would have greater autonomy and, even so, would be able to make an exceptional contribution to the team. Finally, the design thinking approach provided a basis for continuous feedback from end-users, becoming a twofold benefit by triggering new ideas of possible solutions to be deployed onboard.