Task-Oriented Semantic Communication for Hazard Warning and Remote Operation in Connected Vehicle Platoons

task-oriented-semantic-communication-for-hazard-warning-and-remote-operation-in-connected-vehicle-platoons

Task-Oriented Semantic Communication for Hazard Warning and Remote Operation in Connected Vehicle Platoons

[Submitted on 5 Sep 2026 (v1), last revised 27 Oct 2026 (this version, v2)]

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Abstract:Connected and automated vehicle platoons require reliable dissemination of task-relevant hazard information to enable appropriate downstream responses, with unresolved situations additionally requiring remote human intervention. However, the limited channel bandwidth of V2X communication makes high-volume sensor data transmission challenging, motivating the exchange of only task-relevant information rather than raw sensor data. This paper proposes an integrated semantic and task-oriented communication framework for cooperative hazard response and remote operation in automated vehicle platoons. The framework combines onboard instance segmentation and monocular depth estimation for task-oriented hazard decision-making with Stable Diffusion Variational Autoencoder (SD-VAE)-based semantic scene compression. Task-relevant hazard information and the compact semantic representation are jointly disseminated through a broadcast-based Emergency Semantic Message (ESM) over the existing V2X protocol stack. Evaluation demonstrates that SD-VAE consistently outperforms JPEG and JPEG 2000 on task-relevant reconstruction metrics, exhibiting graceful degradation rather than a sharp cliff effect under low-SINR conditions, demonstrating its feasibility for remote scene reconstruction when human intervention is required. Moreover, an extensive campaign of 7,290 simulation runs shows a low overall inter-vehicle collision rate of 0.99%, with collisions occurring mainly under extreme high-speed and short-gap conditions.

Submission history

From: S M Sabit Bananee [view email]
[v1] Sat, 5 Sep 2026 19:53:44 UTC (510 KB)
[v2] Tue, 27 Oct 2026 18:32:58 UTC (510 KB)