Autonomous Driving Systems (ADS) are critical dynamic reconfigurable agent systems whose specification and validation raises extremely challenging problems. The paper presents a multilevel semantic framework for the specification of ADS and discusses associated validation problems. The framework relies on a formal definition of maps modeling the physical environment in which vehicles evolve. Maps are directed metric graphs whose nodes represent positions and edges represent segments of roads. We study basic properties of maps including their geometric consistency. Furthermore, we study position refinement and segment abstraction relations allowing multilevel representation from purely topological to detailed geometric. We progressively define first order logics for modeling families of maps and distributions of vehicles over maps. These are Configuration Logics, which in addition to the usual logical connectives are equipped with a coalescing operator to build configurations of models. We study their semantics and basic properties. We illustrate their use for the specification of traffic rules and scenarios characterizing sequences of scenes. We study various aspects of the validation problem including run-time verification and satisfiability of specifications. Finally, we show links of our framework with practical validation needs for ADS and advocate its adequacy for addressing the many facets of this challenge.

中文翻译：

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自动驾驶系统的规范和验证：多级语义框架

自动驾驶系统 (ADS) 是关键的动态可重构代理系统，其规范和验证提出了极具挑战性的问题。本文提出了 ADS 规范的多级语义框架，并讨论了相关的验证问题。该框架依赖于对车辆发展的物理环境进行建模的地图的正式定义。地图是有向度量图，其节点表示位置，边表示道路段。我们研究地图的基本属性，包括它们的几何一致性。此外，我们研究了位置细化和分段抽象关系，允许从纯拓扑到详细几何的多级表示。我们逐步定义了用于对地图族和车辆在地图上的分布进行建模的一阶逻辑。这些是配置逻辑，除了通常的逻辑连接词之外，它还配备了一个合并运算符来构建模型的配置。我们研究它们的语义和基本属性。我们说明了它们在规范交通规则和表征场景序列的场景中的用途。我们研究验证问题的各个方面，包括运行时验证和规范的可满足性。最后，我们展示了我们的框架与 ADS 的实际验证需求之间的联系，并主张其足以应对这一挑战的许多方面。我们说明了它们在规范交通规则和表征场景序列的场景中的用途。我们研究验证问题的各个方面，包括运行时验证和规范的可满足性。最后，我们展示了我们的框架与 ADS 的实际验证需求之间的联系，并主张其足以应对这一挑战的许多方面。我们说明了它们在规范交通规则和表征场景序列的场景中的用途。我们研究验证问题的各个方面，包括运行时验证和规范的可满足性。最后，我们展示了我们的框架与 ADS 的实际验证需求之间的联系，并主张其足以应对这一挑战的许多方面。