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

arXiv: https://arxiv.org/abs/2609.06242 · HTML: https://mlsanity.com/paper/2609.06242/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 12 of its 22 references that are in the map.
- First posted on arXiv 5 Sep 2026.

## Builds on (most cited first, 12 of 12)

- [High-Resolution Image Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2112.10752/) (2021)
- [Depth Anything V2](https://mlsanity.com/paper/2406.09414/) (2024)
- [BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning](https://mlsanity.com/paper/1805.04687/) (2018)
- [Less Data, More Knowledge: Building Next Generation Semantic Communication Networks](https://mlsanity.com/paper/2211.14343/) (2022)
- [Semantic-Aware Spectrum Sharing in Internet of Vehicles Based on Deep Reinforcement Learning](https://mlsanity.com/paper/2406.07213/) (2024)
- [Adaptable Semantic Compression and Resource Allocation for Task-Oriented Communications](https://mlsanity.com/paper/2204.08910/) (2022)
- [A Multi-Task Oriented Semantic Communication Framework for Autonomous Vehicles](https://mlsanity.com/paper/2403.12997/) (2024)
- [Semantic Communication for Cooperative Perception based on Importance Map](https://mlsanity.com/paper/2311.06498/) (2023)
- [Task-driven Semantic-aware Green Cooperative Transmission Strategy for Vehicular Networks](https://mlsanity.com/paper/2307.15284/) (2023)
- [SComCP: Task-Oriented Semantic Communication for Collaborative Perception](https://mlsanity.com/paper/2507.00895/) (2025)
- [Joint User Association and Bandwidth Allocation in Semantic Communication Networks](https://mlsanity.com/paper/2212.14142/) (2022)
- [Features Disentangled Semantic Broadcast Communication Networks](https://mlsanity.com/paper/2303.01892/) (2023)

## Abstract (arXiv)

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.