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物理意识的时空一致性用于可转移的自动驾驶感知防御
Yang Liu1, Zishan Nie1, Tong Yu2
1Hubei Key Laboratory of Internet of Intelligence, School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China.
Sensors (Basel, Switzerland)
|February 13, 2026
概括
本研究介绍了自动驾驶感知系统的物理意识防御,通过紧密合视觉和物理数据来增强对抗攻击的稳定性. 这种新的方法显著提高了检测准确性和效率,提供了更安全的自动驾驶体验.
科学领域:
- 计算机视觉 计算机视觉
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
背景情况:
- 自动驾驶感知系统面临着对物理对抗攻击的重大脆弱性.
- 当前的防御机制经常使用视觉和动态线索的孤立处理,无法利用物理时空一致性.
- 现有的方法难以平衡对抗性强度,准确性,效率和可转移性与现实的攻击.
研究的目的:
- 为自动驾驶感知提出一种新的物理意识防御系统.
- 通过将视觉语义与物理动态紧密结合起来,增强对物理对手攻击的强度.
- 改善感知系统中时空不一致的检测和纠正.
主要方法:
- 开发了一个物理意识的轨迹-外观一致性防御模块.
- 采用双流时空编码器,具有内源特征编排和频域动态嵌入.
- 引入了轨迹-外观相互排斥 (TAME) 能量来量化不一致性以及用于预测校正的物理意识切换规则.
主要成果:
- 防御模块显著提高了对基准数据集 (nuScenes,KITTI,BDD100K) 的各种对抗性攻击的稳定性.
- 在 nuScenes 上,校正精度 (CA) 从 86.5% 提高到 92.1%,同时计算开销从 42 ms 降低到 19 ms.
- 证明了强大的可转移性,在未见的探测器上保持超过71.0%的CA,并且具有72.4%的CA,对适应性攻击者有弹性.
结论:
- 拟议的物理意识防御有效地检测和纠正时空不一致,增强自动驾驶感知安全性.
- 紧密合视觉和物理动态提供了强大的结构先进性,优于松散合的架构.
- 插电模块提供了一种多功能和高效的解决方案,用于提高现有自动驾驶系统的对抗性强度.
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