AI 中文总结
探讨云能否驱动自动驾驶，通过耦合通信限制、GPU服务模型等构建分析框架，应用于纽约市，研究发现通信、计算、成本依次起约束作用，延迟决定模型可行性，成本决定是否经济。
AI 中文摘要
前沿自动驾驶模型，尤其是前向传递接近60万亿次浮点运算的视觉语言动作（VLA）模型，因大部分时间硬件峰值闲置，已超出经济的车载部署范围。云推理可跨活跃车辆共享GPU，但车辆须通过容量受限的上行链路上传，无排队到达GPU并在闭环预算内返回决策。本文提出能否用云驱动的问题，并通过分析框架耦合通信限制、屋顶线GPU服务模型、随机延迟和利用率感知成本，应用于纽约市。将100毫秒的反应预算与300毫秒的审议层分开，发现三个嵌套的绑定机制。通信在密集小区首先起约束作用，计算在反应预算下起约束作用，成本最后起约束作用。延迟决定哪一年哪种模型可行，成本决定是否经济。
英文摘要
Frontier autonomous-driving models -- especially vision-language-action (VLA) models, whose forward pass approaches $\sim$60~TFLOPs -- are outgrowing economical onboard deployment, since peak hardware sits idle most of the day. Cloud inference can instead share GPUs across active vehicles, but the vehicle must upload through a capacity-limited uplink, reach a GPU without queueing, and return a decision within the closed-loop budget. This paper asks: can the cloud drive? We answer with an analytical framework coupling communication limits, a roofline GPU service model, stochastic latency, and utilization-aware cost across three model classes, three offloading strategies, and three communication generations, applied to New York City. Separating a reactive 100~ms budget from a 300~ms deliberative tier (presuming an onboard reactive fallback), we find three \emph{nested} binding regimes. Communication binds first in dense cells: 5G fails early, 5G-Advanced is the practical threshold for feature-level offloading, and 6G adds headroom. Compute binds next under the reactive budget: near-term VLA is latency-infeasible regardless of bandwidth, because autoregressive FP16 decode is memory-bandwidth-bound (~114 ms on 2025 hardware). Its floor clears 100 ms around 2027; 6G then admits feature-level VLA by ~2028, 5G-Advanced only at light loading and not the dense corridor, and the deliberative tier from 2026. Cost binds last: once admissible, utilization-pooled cloud GPUs undercut onboard hardware for VLA, whose baseline (up to \$8,500 per vehicle-year) is expensive and idle; feature-level offloading (S2) is where the VLA cost crossover concentrates. Latency decides which model is admissible in which year; cost decides whether it is economical.
Comments25 pages, 10 figures
