Abstract
Abstract: Resilience attributes are turned upside down when introducing autonomous maritime transport systems, as technology replaces or assists human functions. We enter an unknown world where we need to rely on autonomous functions and the collaboration between humans and technology. Since less human interaction might cause challenges and effects not yet uncovered, Kaber (2018)[1] discussed levels of autonomy in the context of human automation interaction (HAI). The paper particularly looks at the use of levels of autonomy as taxonomies to structure and improve analysis of human performance, workload, but also situational awareness as well as some of the problems that this may cause. The introduction of increasing automation changes the way human and machine interact in many ways. As such, to ensure resilience in autonomous transport systems, these human and machine interaction challenges must be addressed and systemized, and in this paper the different awareness categories humans, technology and external (Fjørtoft, K.E., 2021), are revisited and linked to resilience. Also, as an extension on how to utilize integrated planning for autonomous transport systems (IPA), as presented by Fjørtoft, et al. (2023), this paper further details emerging issues related to human and machine interface by presenting a framework for how to secure resilience during the design, plan and follow up autonomous ship operations. In other words, the ability to assess and ensure resilience when planning operations in autonomous maritime transport system, while accounting for the interaction between humans and technology. This is of particular relevance due to the likelihood of vessels sailing with different degrees of autonomy, depending on the ongoing operation and its surroundings. Described as operational envelopes in "Towards approval of autonomous ship systems by their operational envelope" (Rødseth 2021), the overall operation must be broken down into sub-operations such as sailing in open seas, berthing, cargo loading/unloading (crane operation), etc.The framework is exemplified through a case study, by combining research results from the Norwegian project MARMAN and EU projects like AUTOSHIP and AEGIS
