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arXiv 2501.06205cs.NIcs.AIcs.CL
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利用边缘智能和LLM推进6G使能的自动化防御车辆互联网

Leveraging Edge Intelligence and LLMs to Advance 6G-Enabled Internet of Automated Defense Vehicles

School of Electrical Engineering and Computer Science University of Ottawa(电气工程与计算机科学学院渥太华大学)

Murat Arda Onsu, Poonam Lohan, Burak Kantarci

AI总结:

本文探讨了在6G和超可靠低延迟通信支持下,结合边缘智能与预训练生成式大型语言模型(LLM)优化军事自动驾驶决策与通信,以推进自动化防御车辆互联网(IoADV)在关键防御应用中的潜力、机遇与挑战。

摘要:

人工智能(AI)及其子集深度学习(DL)的发展深刻影响了包括自动驾驶在内的众多领域。在军事环境中集成自动驾驶可减少人员伤亡,实现在危险环境中精确安全地执行任务,同时提供可靠的后勤支持,避免与疲劳相关的错误风险。然而,仅依赖自动驾驶需要一个在任何情况下都能适应和优化的高级决策模型。考虑到任务关键场景中存在大量互联的自动驾驶车辆,超可靠低延迟通信(URLLC)对于确保无缝协调、实时数据交换和对动态驾驶环境的瞬时响应至关重要。6G的出现通过实现稳健的连接性,加强了军事防御物联网(IoMDT)领域内的自动化防御车辆互联网(IoADV)概念,这种连接性对于通过IoADV交互实现实时数据交换、高级导航和增强安全功能至关重要。另一方面,该领域的一项关键进展是使用预训练的生成式大型语言模型(LLM)进行自动驾驶的决策和通信优化。因此,这项工作提出了机遇和挑战,展望了在关键防御应用中充分发挥这些技术潜力的愿景,特别是通过推进IoADV及其在增强自主军事行动中的作用。

英文摘要:

The evolution of Artificial Intelligence (AI) and its subset Deep Learning (DL), has profoundly impacted numerous domains, including autonomous driving. The integration of autonomous driving in military settings reduces human casualties and enables precise and safe execution of missions in hazardous environments while allowing for reliable logistics support without the risks associated with fatigue-related errors. However, relying on autonomous driving solely requires an advanced decision-making model that is adaptable and optimum in any situation. Considering the presence of numerous interconnected autonomous vehicles in mission-critical scenarios, Ultra-Reliable Low Latency Communication (URLLC) is vital for ensuring seamless coordination, real-time data exchange, and instantaneous response to dynamic driving environments. The advent of 6G strengthens the Internet of Automated Defense Vehicles (IoADV) concept within the realm of Internet of Military Defense Things (IoMDT) by enabling robust connectivity, crucial for real-time data exchange, advanced navigation, and enhanced safety features through IoADV interactions. On the other hand, a critical advancement in this space is using pre-trained Generative Large Language Models (LLMs) for decision-making and communication optimization for autonomous driving. Hence, this work presents opportunities and challenges with a vision of realizing the full potential of these technologies in critical defense applications, especially through the advancement of IoADV and its role in enhancing autonomous military operations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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