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.
@article{arxiv.2205.03347,
title = {Zhuyi: Perception Processing Rate Estimation for Safety in Autonomous Vehicles},
author = {Yu-Shun Hsiao and Siva Kumar Sastry Hari and Michał Filipiuk and Timothy Tsai and Michael B. Sullivan and Vijay Janapa Reddi and Vasu Singh and Stephen W. Keckler},
journal= {arXiv preprint arXiv:2205.03347},
year = {2022}
}
Comments
2022 Design Automation Conference (DAC), July 10-14, 2022, San Francisco