Collision avoidance on maritime autonomous surface ships: Operators’ tasks and human failure events

Abstract

Numerous research and industry initiatives have increasingly aimed at developing maritime surface autonomous ships (MASS). Among the motivations for the use of MASS is the potential increase in safety when compared to traditional manned ships – particularly regarding human error. However, in spite of having less human intervention, MASS will rely on humans working on an onshore control center for their operation. There have been great advances in investigating the technical aspects of MASS operation, such as collision avoidance algorithms and detection sensors; nevertheless, possible human tasks and their deriving failures have rarely been addressed. This paper thus explores how humans can be a key factor for successful collision avoidance in future MASS operations. It presents a task analysis for collision avoidance through Hierarchical Task Analysis and making use of a cognitive model for categorizing the tasks. The failures in accomplishing these tasks are further analyzed, and human failure events are identified. The results provide valuable information for the design stage of the system; which must acknowledge the operators’ tasks to ensure a safe voyage. The conclusions of this paper are also a starting point for the implementation of a Human Reliability Analysis for this operation.