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The study surveyed maritime professionals on their attitudes toward AI‑supported decision assistants in collision‑avoidance scenarios. Results show a generally positive disposition toward maritime technology, stable trust across scenarios, and nuanced, scenario‑sensitive ratings of explanation quality. Open‑ended feedback highlighted the importance of decision‑support, situational awareness, and confidence‑building, while raising concerns about AI reliability, over‑reliance, and loss of expertise.
arXiv:2607. 26121v1 Announce Type: cross Abstract: Embodied intelligence integrates learned perception and decision making with real-time computation, control, and physical interaction.
arXiv:2609.13552v1 Announce Type: new Abstract: Generative AI is increasingly being used informally in Air Traffic Management (ATM) for tasks such as flight plan generation, trajectory interpretation...
arXiv:2606. 00090v1 Announce Type: cross Abstract: Physical AI systems increasingly map multimodal observations, language instructions, and learned world representations into physically consequential actions.
arXiv:2408. 12548v3 Announce Type: replace Abstract: Machine Learning (ML) has become central to Autonomous Vehicles (AVs), supporting perception, prediction, planning, control, and decision-making in dynamic environments.
Large language model (LLM) agents may assist flight crews with complex decisions and task execution, but existing aviation evaluations centered on static knowledge do not support systematic testing of...