论文标题
Zhuyi：自动驾驶汽车安全性的感知处理率估计
Zhuyi: Perception Processing Rate Estimation for Safety in Autonomous Vehicles
论文作者
论文摘要
在复杂方案中，自动驾驶汽车（AV）的处理要求（AVS）可以超过车载计算机提供的资源，从而使安全性和舒适性降低。本文提出了传感器框架处理速率（FPR）估计模型Zhuyi，该模型在驾驶场景中连续量化最小安全FPR。 Zhuyi可以作为在线安全检查并确定工作的优先级。使用多摄像机的最先进的行业AV系统进行的实验表明，Zhuyi的估计FPR是保守的，但是与经过测试的方案相比，该系统可以通过处理仅36％或更少的帧来维持安全性。
The processing requirement of autonomous vehicles (AVs) for high-accuracy perception in complex scenarios can exceed the resources offered by the in-vehicle computer, degrading safety and comfort. This paper proposes a sensor frame processing rate (FPR) estimation model, Zhuyi, that quantifies the minimum safe FPR continuously in a driving scenario. Zhuyi can be employed post-deployment as an online safety check and to prioritize work. Experiments conducted using a multi-camera state-of-the-art industry AV system show that Zhuyi's estimated FPRs are conservative, yet the system can maintain safety by processing only 36% or fewer frames compared to a default 30-FPR system in the tested scenarios.
