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新arXiv论文详述AI赋能的城市交通数字孪生

一篇新发表在arXiv上的研究论文详细介绍了为城市交通管理开发AI赋能的数字孪生。该论文强调了这些数字孪生“大脑”的重要性,它涉及预测和决策能力,而不仅仅是感知和识别。论文提出,将人工智能与网络物理系统集成对于创建有效的数字孪生至关重要,这些数字孪生可以通过识别模式和辅助决策来增强城市交通管理。 AI

影响 这项研究可能通过先进的AI驱动的模拟和决策,带来更高效、更具响应性的城市交通系统。

排序理由 研究论文,详述了AI赋能的数字孪生的方法和应用。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新arXiv论文详述AI赋能的城市交通数字孪生

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研究论文,详述了AI赋能的数字孪生的方法和应用。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yongjie Fu, Mehmet K. Turkcan, Mahshid Ghasemi, Zhaobin Mo, Chengbo Zang, Abhishek Adhikari, Zoran Kostic, Gil Zussman, Xuan Di ·

    人工智能驱动的CPS赋能的易受攻击用户感知城市交通数字孪生:方法与应用

    arXiv:2501.10396v4 Announce Type: replace-cross Abstract: We present methods and applications for the development of digital twins (DT) for urban traffic management. While the majority of studies on the DT focus on its ``eyes," which is the emerging sensing and perception like ob…