SwarmDrive: Semantic V2V Coordination for Latency-Constrained Cooperative Autonomous Driving

TL;DR

SwarmDrive introduces a semantic V2V coordination framework using local language models and event-triggered consensus to improve autonomous driving performance under latency constraints.

Contribution

It presents a novel semantic V2V coordination method that balances latency, robustness, and communication overhead in autonomous driving scenarios.

Findings

SwarmDrive increases success rate from 68.9% to 94.1% in occluded intersection scenarios.

Latency is reduced from 510 ms to 151.4 ms compared to cloud-based inference.

Optimal swarm size and entropy threshold are identified for best performance.

Abstract

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% to 94.1% over a single local SLM while reducing latency from a 510 ms cloud reference to 151.4 ms. However, an increased number of participating vehicles leads to higher communication overhead and packet loss. SwarmDrive also evaluates the impact of swarm-size, packet-loss, and entropy-threshold sweeps and shows that the cooperative gain holds across ablations and is best balanced near an active swarm size of 4 vehicles and an entropy trigger threshold of 0.65 in the current prototype. These results show that semantic edge cooperation can work under tight latency constraints in the targeted intersection case, but they are not a deployment-grade validation of a real 6G stack.