NICVSYOct 21, 2024

Managing Bandwidth: The Key to Cloud-Assisted Autonomous Driving

arXiv:2410.16227v13 citationsh-index: 63
Originality Incremental advance
AI Analysis

This addresses the challenge of real-time control in self-driving cars for automotive and cloud industries, but it appears incremental as it builds on existing trends in hardware and networks.

The paper tackles the problem of enabling cloud-assisted autonomous driving by proposing bandwidth management to meet strict latency requirements, arguing that offloading compute to the cloud is feasible and necessary despite traditional skepticism.

Prevailing wisdom asserts that one cannot rely on the cloud for critical real-time control systems like self-driving cars. We argue that we can, and must. Following the trends of increasing model sizes, improvements in hardware, and evolving mobile networks, we identify an opportunity to offload parts of time-sensitive and latency-critical compute to the cloud. Doing so requires carefully allocating bandwidth to meet strict latency SLOs, while maximizing benefit to the car.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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