SwarmDrive: Semantic V2V Coordination for Latency-Constrained Cooperative Autonomous Driving
Cloud-hosted LLM inference for autonomous driving adds round-trip delay and depends on stable connectivity, while purely local edge models struggle under occlusion. We present SwarmDrive, a semantic Vehicle-to-Vehicle (V2V) coordination framework in which nearby vehicles run local Small Language Models (SLMs), share compact intent distributions only when uncertainty is high, and fuse them through event-triggered consensus. We evaluate SwarmDrive in a 5-seed executable study built around one occluded intersection case, combining matched operating-point comparisons with robustness sweeps. In that setting, SwarmDrive under its 6G communication setting ("Swarm 6G") raises success from 68.9% t...
| Authors | Anjie Qiu, Donglin Wang, Zexin Fang et al. |
|---|---|
| Primary category | cs.RO |
| Published | 22 April 2026 |
| Last updated at source | 22 April 2026 |
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