论文标题
从安全性和可靠性的角度评估对象（MIS）检测：讨论和措施
Evaluating Object (mis)Detection from a Safety and Reliability Perspective: Discussion and Measures
论文作者
论文摘要
我们认为，安全临界域中的对象探测器应优先考虑检测最有可能干扰自主行为行为的对象。特别是，这适用于可能影响演员安全性和可靠性的对象。为了量化对象（MIS）检测对自动驾驶的安全性和可靠性的影响，我们提出了新的对象检测指标，以奖励正确识别最危险的对象，并且最有可能影响驾驶决策。为了实现这一目标，我们建立了一个对象临界模型，以奖励基于邻近性，方向和相对速度相对于主体车辆的检测。然后，我们将模型应用于最近的自动驾驶数据集Nuscenes，并比较九个对象检测器。结果表明，在几种设置中，当焦点转移到安全性和可靠性上时，根据Nuscenes排名表现最佳的对象探测器并不是可取的。
We argue that object detectors in the safety critical domain should prioritize detection of objects that are most likely to interfere with the actions of the autonomous actor. Especially, this applies to objects that can impact the actor's safety and reliability. To quantify the impact of object (mis)detection on safety and reliability in the context of autonomous driving, we propose new object detection measures that reward the correct identification of objects that are most dangerous and most likely to affect driving decisions. To achieve this, we build an object criticality model to reward the detection of the objects based on proximity, orientation, and relative velocity with respect to the subject vehicle. Then, we apply our model on the recent autonomous driving dataset nuScenes, and we compare nine object detectors. Results show that, in several settings, object detectors that perform best according to the nuScenes ranking are not the preferable ones when the focus is shifted on safety and reliability.
