Zhuyi: Perception Processing Rate Estimation for Safety in Autonomous Vehicles

May 06, 2022 Β· Declared Dead Β· πŸ› Design Automation Conference

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Authors Yu-Shun Hsiao, Siva Kumar Sastry Hari, MichaΕ‚ Filipiuk, Timothy Tsai, Michael B. Sullivan, Vijay Janapa Reddi, Vasu Singh, Stephen W. Keckler arXiv ID 2205.03347 Category cs.AI: Artificial Intelligence Cross-listed cs.RO Citations 5 Venue Design Automation Conference Last Checked 4 months ago
Abstract
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.
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