Intelligent Operator Support Concepts for Shore Control Centres

Abstract

Abstract This paper introduces three intelligent operator support functions to allow multiple operators to effectively and efficiently supervise multiple autonomous operations. The many-to-many concept assumes a stage in human-automation collaboration design where supervision of maritime autonomous surface ships is not permanently required anymore. Only in extreme and very rare situations the human may need to intervene. One of the challenges is balancing the task assignments and support functions over the operators to ensure the cognitive task load matches the operator’s mental capacity. For this purpose we introduce and described a dynamic task allocation algorithm. Also, human attention is limited and operators therefore must constantly shift attention resulting in moment-to-moment fluctuations in situation awareness. To overcome these reductions in situation awareness, operators must reassess the environment to recover situation awareness. We introduce the concept of continuous risk assessment to initiate the process of situation awareness recovery. Furthermore, the many-to-many ratio between supervising operators and autonomous ships implies that operators will not be able to supervise all ships in parallel. This makes current supervisory control interfaces less suitable. Instead we opt to apply the idea of progressive disclosure in the operator’s interface and interactions. The work described in this paper is directed towards developing an intelligent operator support system with which the operator support functions will be demonstrated as part of a Robotic Container Handling System, an innovation of the European MOSES research project.