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Safety Score: A Quantitative Approach to Guiding Safety-Aware Autonomous Vehicle Computing System Design

机译:安全分数:一种指导安全意识自动车辆计算系统设计的定量方法

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High automated vehicles rely on the computing system in the car to understand the environment and make driving decisions. Therefore, computing system design is essential for ensuring the driving safety. However, to our knowledge, no clear guideline exists so far regarding how to guide the safety-aware autonomous vehicle (AV) computing system design. To understand the safety requirement of AV computing system, we performed a field study by operating industrial Level-4 AV fleets in multiple locations for three months. The field study indicates that traditional computing system performance metrics, such as tail latency, average latency, maximum latency, and timeout, cannot fully satisfy the safety requirement for AV computing system design. To address this issue, we propose the “safety score” as a primary metric for measuring the level of safety in AV computing system design.
机译:高自动化车辆依靠汽车中的计算系统来了解环境并制定驾驶决策。因此,计算系统设计对于确保驾驶安全性至关重要。但是,到目前为止,到目前为止,目前没有关于如何引导安全意识自动车辆(AV)计算系统设计的明确指南。要了解AV计算系统的安全要求,我们通过在多个地点运行三个月的工业等级-4 AV车队进行了一个现场研究。现场研究表明,传统的计算系统性能指标,如尾延迟,平均延迟,最大延迟和超时,不能完全满足AV计算系统设计的安全要求。为解决此问题,我们提出了“安全分数”作为测量AV计算系统设计中安全水平的主要指标。

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