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.
By Doreen Jirak, Armeen Saroukanoff, Dirk van Rooy
arXiv:2607. 26121v1 Announce Type: cross Abstract: Embodied intelligence integrates learned perception and decision making with real-time computation, control, and physical interaction.
By Xinyu Yang, Tianxing Chen, Honghao Su, Minxuan Wang, Chenze Yu, Zhangzheng Tu, Yue Chen, Yuxiao Huo, Lingfeng Zhang, Yan Huang, Yan Qin, Shaolong Zhu, Qiwei Liang, Hekun Tian, Shujia Liu, Guangyu Chen, Junhao Gong, Zixuan Li, Wenwei Lin, Zijian Lin, Wenxuan Zhu, Eric J Chen, Yue Yuan, Qize Yu, Jiaqi Liang, Haowen Yan, Hengfei Zhao, Weijie Wan, Zikun Xiao, Junyuan Tang, Baijun Chen, Kai-Chong Lei, Kaixuan Wang, Kailun Su, Zanxin Chen, Yao Mu, Renjing Xu, Chuqiao Lyu, Qi Xiong, Ping Luo, Wenbo Ding
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...
By Alexandre Barreto (George Mason University), Shou Matsumoto (George Mason University), Jorge Valverde-Rebaza (Tecnol\'ogico de Monterrey), Cleiton Ataide (DECEA: Department of Airspace Control), Paulo Costa (George Mason University)
arXiv:2606. 00090v1 Announce Type: cross Abstract: Physical AI systems increasingly map multimodal observations, language instructions, and learned world representations into physically consequential actions.
By Barak Or
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.
By Yousef Emami, Mohammadhossein Homaei, Miguel Guti\'errez Gait\'an, Luis Almeida, Kai Li, Hui Huang, Zhu Han
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...
arXiv:2610.08363v1 Announce Type: new
Abstract: Maritime systems operate in highly dynamic environments where unexpected equipment failures can compromise safety, reliability, and operational efficie...
By Dionisis Kalogeropoulos, Georgia Sovatzidi, Panagiotis G. Kalozoumis, Dimitris K. Iakovidis
arXiv:2608. 16349v1 Announce Type: new Abstract: 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 procedural execution and safety compliance in interactive environments.
By Yuchen Yuan, Zhenghuang Wu, Yuangan Li, Liang Ma, Ke Li
The paper introduces TRACE, a Transparent Reasoning Architecture for Credible Execution, which provides an explainable AI-based decision framework for autonomous robots. TRACE structures decision-making into four auditable layers—Semantic Perception, Belief Reasoning, Action Synthesis, and Execution Verification—to ensure every action can be traced back to sensor evidence through documented causal chains. Experimental results on warehouse robot navigation show high evidence traceability (98.6%), temporal continuity (99.0%), and decision reconstructability (98.1%) across 500 simulated decision cycles.
By Cagri Temel
arXiv:2608. 06105v1 Announce Type: cross Abstract: Artificial Intelligence (AI)-assisted navigation can help Arctic shipping adapt to rapidly changing sea-ice conditions, but reliable deployment requires reward models that are interpretable and robust to changing environments.
By Vaishnav Vaidheeswaran, Dilith Jayakody, Biruk Ambaw, Jaswanth Kumar, Md Mahbub Alam, Gabriel Spadon
arXiv:2505. 23397v3 Announce Type: replace Abstract: This article presents a structured framework for Human-AI collaboration in Security Operations Centers (SOCs), integrating AI autonomy, trust calibration, and Human-in-the-loop decision making.
By Ahmad Mohsin, Helge Janicke, Ahmed Ibrahim, Iqbal H. Sarker, Seyit Camtepe
arXiv:2610.28121v1 Announce Type: new
Abstract: Safe autonomous navigation of UASs requires tactical deconfliction to address conflicts that strategic coordination cannot prevent. This task is challe...
By Christopher Conrad, Deepak Panda, Weisi Guo, Antonios Tsourdos