Decision-making while interacting with unmanned vessels
Authors: Fernando Plácido Da Conceição Vítor , Sousa Beatriz , Água Pedro , Dahlman Joakim 
Published: July 2023

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.