论文标题
传感器，安全模型和系统级别的方法，用于安全可扩展的自动化车辆
Sensors, Safety Models and A System-Level Approach to Safe and Scalable Automated Vehicles
论文作者
论文摘要
在考虑自动化车辆（AV）中传感器的准确性时，不足以隔离任何给定传感器的性能。相反，必须在整个系统设计的背景下考虑任何单个传感器的性能。冗余和不同感应方式等技术可以减少感应失败的机会。此外，使用安全模型对于了解任何特定的感应失败是否相关至关重要。只有当考虑整个系统设计时，只有一个人才能正确理解与安全相关的感应失败的含义。在本文中，我们将考虑应实际构成感应失败的原因，安全模型如何在减轻潜在故障的情况下发挥重要作用，系统级安全方法如何提供安全可扩展的AV，以及可接受的感应失败率应该考虑AV架构的完整图片。
When considering the accuracy of sensors in an automated vehicle (AV), it is not sufficient to evaluate the performance of any given sensor in isolation. Rather, the performance of any individual sensor must be considered in the context of the overall system design. Techniques like redundancy and different sensing modalities can reduce the chances of a sensing failure. Additionally, the use of safety models is essential to understanding whether any particular sensing failure is relevant. Only when the entire system design is taken into account can one properly understand the meaning of safety-relevant sensing failures in an AV. In this paper, we will consider what should actually constitute a sensing failure, how safety models play an important role in mitigating potential failures, how a system-level approach to safety will deliver a safe and scalable AV, and what an acceptable sensing failure rate should be considering the full picture of an AV's architecture.
