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English(EN) FaultGene: LLM-Assisted Fault-Augmented Test Generation for Hardware-in-the-Loop Validation of Autonomous Driving Systems

LLM辅助框架自动化自动驾驶系统测试

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了FaultGene，一个使用大型语言模型（LLMs）自动创建故障增强测试用例来验证自动驾驶系统的新框架。该方法通过实现硬件在环（HIL）验证，解决了纯物理或模拟测试的局限性。FaultGene接收现有的驾驶场景和故障规范，生成可执行的测试，以捕捉硬件故障的影响，提高测试覆盖率和效率。 AI

影响 自动化生成自动驾驶系统的复杂测试用例，可能加速验证并提高安全性。

排序理由 该集群描述了一篇详细介绍新的自动化测试生成框架的研究论文。

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

LLM辅助框架自动化自动驾驶系统测试

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该集群描述了一篇详细介绍新的自动化测试生成框架的研究论文。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Chaoran Yuan, Fadi Kurdahi ·

    FaultGene: LLM-Assisted Fault-Augmented Test Generation for Hardware-in-the-Loop Validation of Autonomous Driving Systems

    arXiv:2610.29969v1 Announce Type: cross Abstract: Reliable validation of autonomous driving cyber-physical systems requires testing not only nominal driving behavior but also failures arising from faults in sensing and embedded computation. Physical road testing provides realisti…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    FaultGene: LLM-Assisted Fault-Augmented Test Generation for Hardware-in-the-Loop Validation of Autonomous Driving Systems

    Reliable validation of autonomous driving cyber-physical systems requires testing not only nominal driving behavior but also failures arising from faults in sensing and embedded computation. Physical road testing provides realistic system behavior but is costly and difficult to r…

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