arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2401.04875cs.SE
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基于Event-B细化的责任感知自动驾驶汽车安全架构形式化建模

Formal Modelling of Safety Architecture for Responsibility-Aware Autonomous Vehicle via Event-B Refinement

Tsutomu Kobayashi, Martin Bondu, Fuyuki Ishikawa

AI总结:

本文针对自动驾驶汽车在复杂交通场景下的安全形式化证明难题,提出利用Event-B细化机制建模并推导安全条件,结合目标感知责任敏感安全模型与Simplex架构引入AI黑盒控制器,证明了该机制能逐步有效开发复杂系统。

摘要:

确保自动驾驶汽车(AVs)的安全是其被社会接受的关键前提。在AI黑盒控制器和周围物体处于各种交通场景下,这种复杂性是形式化证明其安全条件的核心挑战。本文描述了我们在建模、推导和证明AVs安全条件方面的策略与经验,利用Event-B细化机制来降低复杂性。我们的案例研究以目标感知责任敏感安全的最先进模型为目标,论证与周围车辆的交互。我们还采用Simplex架构来引入先进的黑盒AI控制器。经验表明,细化机制能有效用于在场景变化中逐步开发复杂系统。

英文摘要:

Ensuring the safety of autonomous vehicles (AVs) is the key requisite for their acceptance in society. This complexity is the core challenge in formally proving their safety conditions with AI-based black-box controllers and surrounding objects under various traffic scenarios. This paper describes our strategy and experience in modelling, deriving, and proving the safety conditions of AVs with the Event-B refinement mechanism to reduce complexity. Our case study targets the state-of-the-art model of goal-aware responsibility-sensitive safety to argue over interactions with surrounding vehicles. We also employ the Simplex architecture to involve advanced black-box AI controllers. Our experience has demonstrated that the refinement mechanism can be effectively used to gradually develop the complex system over scenario variations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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