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GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
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Collaborative Work with Highly Automated Marine Navigation Systems.

Erik Veitch1, Henrikke Dybvik2, Martin Steinert2

  • 1Department of Design, Faculty of Architecture and Design, Norwegian University of Science and Technology (NTNU), Produktdesign, 341, Gløshaugen, Kolbjørn Hejes Vei 2 B, 7491 Trondheim, Norway.

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Summary
This summary is machine-generated.

Artificial Intelligence (AI) in navigation can enhance efficiency, but designers and navigators differ on human-AI collaboration. Navigators act as backup, taking over control, while designers overlook in-situ skills, impacting AI integration.

Keywords:
Artificial intelligenceAutonomous shipsCollaborative workControl roomsHuman–computer interactionInteraction designNavigation

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Area of Science:

  • Maritime technology
  • Human-computer interaction
  • Artificial Intelligence (AI)

Background:

  • AI integration in navigation aims to improve efficiency and decision-making.
  • Understanding human-AI collaboration is crucial for effective AI system design in maritime operations.

Purpose of the Study:

  • To investigate the transition towards increased machine autonomy in the maritime sector.
  • To examine the discrepancies in understanding human-AI collaboration between technology designers and navigators.

Main Methods:

  • Empirical study involving interviews with 9 technology designers and 5 navigators.
  • Field observations conducted aboard two partially automated ferries.
  • Analysis of navigators' roles and designers' perspectives on AI integration.

Main Results:

  • A significant gap exists between designers' and navigators' views on human-AI cooperation.
  • Navigators perceive their role as 'backup,' involving ad-hoc control takeovers.
  • Designers' models often underestimate the navigators' in-situ skills and heuristic decision-making.

Conclusions:

  • AI system design should better align with human cooperation by increasing visibility of computational activities.
  • Incorporating social cues in AI design can better articulate human work in natural settings.
  • Findings offer insights for human-AI interaction design in future navigation and control room work.