论文标题

部分可观测时空混沌系统的无模型预测

Reliability of fault-tolerant system architectures for automated driving systems

论文作者

Julitz, Tim Maurice, Tordeux, Antoine, Löwer, Manuel

论文摘要

高水平自治的自动驾驶功能在没有驾驶员监督的情况下运行。在硬件元素失败的情况下,系统本身必须提供合适的响应。这需要使用域ECU和以LockStep模式运行的多层处理器进行易于故障的方法。目前,选择适合耐故障车辆系统的合适体系结构具有挑战性。 Lockstep CPU允许实施多数冗余或n的M $ $ oo $ $ n $)架构。除结构冗余外,ECU架构中的多样性冗余也与容错性有关。存在两个容忍性的ECU架构组:具有一个ECU(芯片上的系统)和由多个通信ECU组成的体系结构。单一ECU系统具有更高的可靠性,而多ECU系统则更强大地抵抗依赖性故障,例如普通原因或级联故障,因为它们增加了多样性冗余的潜力。但是,尚不完全了解不同类型的体系结构如何影响系统的可靠性。这项工作旨在设计有关CPU和传感器编号,$ m $ oo $ n $表达式以及硬件元素可靠性的架构。结果可以直接比较不同的体系结构类型。我们计算它们的可靠性,并量化达到高安全要求的努力。 Markov过程允许通过改变组件和故障率的数量来比较传感器和CPU架构。目的是评估系统的生存概率和容错性,并设计合适的传感器-CPU架构。结果表明,系统体系结构强烈影响可靠性。但是,合适的系统体系结构必须在可靠性和自我诊断之间进行权衡,而这些系统与没有多数裁员的系统并不提供。

Automated driving functions at high levels of autonomy operate without driver supervision. The system itself must provide suitable responses in case of hardware element failures. This requires fault-tolerant approaches using domain ECUs and multicore processors operating in lockstep mode. The selection of a suitable architecture for fault-tolerant vehicle systems is currently challenging. Lockstep CPUs enable the implementation of majority redundancy or M-out-of-N ($M$oo$N$) architectures. In addition to structural redundancy, diversity redundancy in the ECU architecture is also relevant to fault tolerance. Two fault-tolerant ECU architecture groups exist: architectures with one ECU (system on a chip) and architectures consisting of multiple communicating ECUs. The single-ECU systems achieve higher reliability, whereas the multi-ECU systems are more robust against dependent failures, such as common-cause or cascading failures, due to their increased potential for diversity redundancy. Yet, it remains not fully understood how different types of architectures influence the system reliability. The work aims to design architectures with respect to CPU and sensor number, $M$oo$N$ expression, and hardware element reliability. The results enable a direct comparison of different architecture types. We calculate their reliability and quantify the effort to achieve high safety requirements. Markov processes allow comparing sensor and CPU architectures by varying the number of components and failure rates. The objective is to evaluate systems' survival probability and fault tolerance and design suitable sensor-CPU architectures. The results show that the system architecture strongly influences the reliability. However, a suitable system architecture must have a trade-off between reliability and self-diagnostics that parallel systems without majority redundancies do not provide.

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