利用时空感知逻辑对自动驾驶汽车感知系统的要求进行形式化和评估

Mohammad Hekmatnejad, Bardh Hoxha, Jyotirmoy V. Deshmukh, Yezhou Yang, Georgios Fainekos
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引用次数: 0

摘要

自动驾驶汽车(AV)在很大程度上依赖于强大的感知系统。目前评估视觉系统的方法主要侧重于逐帧性能。当感知子系统用于自动驾驶汽车时,这些评估方法似乎不足以评估其性能。在本文中,我们提出了一种逻辑,即时空感知逻辑(STPL),它同时利用了空间和时间模式。STPL 可以使用空间和时间运算符对感知数据进行推理。STPL 的一个主要优势是,它有助于对感知系统的功能性能进行基本的正确性检查,即使在某些情况下没有基本真实数据。我们确定了 STPL 的一个片段,该片段可在多项式时间内高效离线监控。最后,我们介绍了一系列视听感知系统的规范,以强调通过 STPL 离线监测可以表达和分析的需求类型。
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Formalizing and evaluating requirements of perception systems for automated vehicles using spatio-temporal perception logic
Automated vehicles (AV) heavily depend on robust perception systems. Current methods for evaluating vision systems focus mainly on frame-by-frame performance. Such evaluation methods appear to be inadequate in assessing the performance of a perception subsystem when used within an AV. In this paper, we present a logic—referred to as Spatio-Temporal Perception Logic (STPL)—which utilizes both spatial and temporal modalities. STPL enables reasoning over perception data using spatial and temporal operators. One major advantage of STPL is that it facilitates basic sanity checks on the functional performance of the perception system, even without ground truth data in some cases. We identify a fragment of STPL which is efficiently monitorable offline in polynomial time. Finally, we present a range of specifications for AV perception systems to highlight the types of requirements that can be expressed and analyzed through offline monitoring with STPL.
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