论文标题
提高基于DNN的感知的策略
Strategy to Increase the Safety of a DNN-based Perception for HAD Systems
论文作者
论文摘要
安全是高度自动驾驶（HAS）系统最重要的开发目标之一。这特别适用于深神网络（DNN）驱动的感知函数。对于这些，传统的安全过程和要求的大部分不完全适用或足够。本文的目的是提出一个框架，用于描述和缓解DNN不足的情况以及相关安全机制的推导以提高DNN的安全性。为了评估这些安全机制的有效性，我们提出了评估指标的分类方案。
Safety is one of the most important development goals for highly automated driving (HAD) systems. This applies in particular to the perception function driven by Deep Neural Networks (DNNs). For these, large parts of the traditional safety processes and requirements are not fully applicable or sufficient. The aim of this paper is to present a framework for the description and mitigation of DNN insufficiencies and the derivation of relevant safety mechanisms to increase the safety of DNNs. To assess the effectiveness of these safety mechanisms, we present a categorization scheme for evaluation metrics.
