Human-Machine Interface Considerations for Design and Testing in Distributed Sociotechnical Systems
Abstract: The increasing concerns for safety and environmental sustainability create demands on the development of future maritime transportation strategies. One way to meet these demands is the concept of autonomous unmanned vessels for intercontinental voyages. As automation is being introduced onboard and watch keeping operations being migrated to the shore, there is a risk introducing new human factor issues among the various stakeholder groups and add to the complexity of the actors’ roles. This licentiate was based on the context of an EU research project MUNIN (Maritime Unmanned Ship through Intelligence in Networks) about remote monitoring and controlling autonomous unmanned ships where the bridge and engine control room were moved from the ship to a land based control station. Human Machine Interface, as a mediating artefact in the complex system to bridge automation/engine control is of importance for situation awareness, reliability, efficiency, effectiveness, resilience and safety. The purpose of the thesis is to achieve a comprehensive understanding of the complexity of Human Machine Interface in a distributed complex system by exploring the experiences of the human agents during the designing and testing phases of a designed for purpose Human Machine Interface. The results reveal prominent human factor issues related to situation awareness and automation bias within such a complex distributed sociotechnical system, which sheds light on the design considerations of Human Machine Interface. Loss of presence can lead to critical perceptual bottlenecks which could negatively impact upon the operators; the organizational factors also greatly shape individual and team performance. It indicates that the contextual factors in the distributed sociotechnical system must be accommodated by the interface design through a holistic systemic approach. The Human Machine Interface shall not only support data visualization, but also the process and context in which data are utilized and understood for consensus decision-making.
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