The connected IP train and interdependent integration at the control centre

AbstractArtificial intelligence is transforming how we interact with vehicles. We examine the case of Maritime Autonomous Surface Ships (MASS), which are emerging as a safer and more effective solution for maritime transportation. Despite the focus on autonomy, humans are predicted to have a central role in MASS operations from a Shore Control Centre (SCC). Here, operators will provide back-up control in the event of system failure. There are signification design challenges with such a system. The most critical is human-system interaction in autonomy (H-SIA). We consider humans as the source of resilience in the system for adapting to unexpected events and managing safety. We ask, can Human-Centred Design (HCD) be used to create resilient interactions between MASS and SCC? Work has been done in resilience engineering for complex systems but has not been extended to H-SIA in transportation. “Resilient interaction design” is relevant as we progress from design to operational phase. We adopted the ISO 9421-210 guideline to structure our HCD approach. The result is an SCC designed for 1 Autonomy Operator (AO). The contribution is a demonstration of how resilient interaction design may lead to safer and more effective H-SIA in transportation.

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Autonomous ships for container shipping in the Arctic routes

Journal of Marine Science and Technology ◽

10.1007/s00773-021-00836-8 ◽

2021 ◽

Author(s):

Ziaul Haque Munim ◽

Rana Saha ◽

Halvor Schøyen ◽

Adolf K. Y. Ng ◽

Theo E. Notteboom

Keyword(s):

Environmental Protection ◽

Search And Rescue ◽

The Arctic ◽

Multi Criteria Decision Making ◽

Container Shipping ◽

Foreseeable Future ◽

Arctic Shipping ◽

Control Centre ◽

Autonomous Ship ◽

Best Worst Method

AbstractThis study investigates the competitiveness of various autonomous ship categories for container shipping in the Arctic route. We propose a multi-criteria decision-making (MCDM) framework using four ship categories as alternatives and eight criteria for competitiveness evaluation. We analyse collected data using the Best–Worst Method (BWM), one of the recently developed MCDM methods. The findings reveal that operating expenses, navigation aspects, and environmental protection are the three most important criteria for deploying autonomous ships in the Arctic route. Among the three investigated autonomous ships alternatives, the semi-autonomous ship operated from a shore control centre (SCC) is prioritized for Arctic shipping in the foreseeable future, when benchmarked against the conventional ship. The SCC-controlled semi-autonomous ship alternative is competitive in the majority of the considered criteria including operating expenses, capital expenses, navigation, ship-shore and ship–ship communication, search and rescue, and environmental protection.

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