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.
翻译:机动车辆在复杂情况下对高准确度认知的处理要求可能超过车辆内计算机、有辱人格的安全和舒适提供的资源,本文件提议了一个传感器框架处理率(FPR)估计模型,Zhuyi, 该模型在驾驶的情况下连续对最低安全FPR进行量化。Zhuyi可以在部署后作为在线安全检查和确定工作的优先次序。使用多光子最先进的AV系统进行的实验表明,Zhuyi的估计FPR是保守的,但该系统只能通过处理36%或更少的框架来维持安全,而测试的假设情况下的默认30-FPR系统则只有36%或更少的框架。