As autonomous systems are increasingly integrated into blue economy industries, and maritime transport advances toward Maritime Autonomous Surface Ships (MASS), the central role of human factors are often overlooked in industry discussions. Improved livelihoods, job creation, and maritime safety are fundamental themes across the sectors of the blue economy, all of which will be influenced by autonomous vessels. The proposed four degrees of MASS will incrementally reduce human effort onboard and increase overall ship autonomy, transforming the roles and responsibilities of human operators from direct onboard operation to human oversight of algorithm-driven autonomy. This transition creates a new type of interaction where human operators are managing multiple displays and alarm systems, while maintaining the delicate equilibrium between reliance, caution, and situational awareness. Appropriate trust in automation is central to this interaction, as both excessive and insufficient trust can result in unsafe human behaviours.

While it is widely agreed that trust incorporates an element of risk, the interplay between distinct elements of risk and trust remain underexplored. Given the complexity and safety-critical nature of maritime operations, this gap underscores the need for empirical studies that inform the training of seafarers to establish and maintain appropriate trust in automation, in varying risk scenarios. As seafarer responsibilities shift with reducing human presence and increasingly autonomous operations, examining human factors that impact the calibration of trust in human-automation interaction is essential to ensure safety, and inform training and education for the human operators leading the integration of autonomous vessels into blue economy industries.

Objectives

1. Examine the influence of perceived risk on trust in human-automation interactions.
2. Correlate separate constructs of both trust and perceived risk, assessing how they mediate reliance on automation.
3. Compare trust in autonomous systems in mixed-autonomy scenarios external to the ship.
4. Evaluate adaptations to maritime skills, training, and competence frameworks for the unique demands of autonomous shipping.

Outcomes

1. Comprehensive understanding of how risk perception impacts trust in automation.
2. Identify best practice to enhance trust calibration in human-automation interactions.
3. Recommendations for policy, training, and operational protocols to mitigate trust issues in human-automation interactions.