Real-Time Semantic Communication System for Remote Driving

Jiale  Wu; Celimuge Wu; Lei Zhong; Yangfei Lin; Jianhang  Tang; Soufiene Djahel

doi:10.1109/INFOCOM59046.2026.11571175

Real-Time Semantic Communication System for Remote Driving

Jiale Wu
, Celimuge Wu
, Lei Zhong
, Yangfei Lin
, Jianhang Tang
, Soufiene Djahel

Centre for Future Transport and Cities

The University of Electro-Communications
Toyota Motor Corporation
GuiZhou University

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

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Abstract

This paper introduces a real-time semantic communication system for remote driving, addressing the challenges of video transmission over constrained and fluctuating wireless communication links. Instead of transmitting raw video streams, the proposed system extracts and transmits compact semantic representations, significantly reducing bandwidth requirements while preserving task-relevant visual information. An end-to end semantic encoding-decoding pipeline enables low latency operator-view reconstruction with low latency, improving robustness without relying on high-throughput links. Implemented and evaluated on the real-time prototype, the proposed system demonstrates the practicality of semantic communication for enhancing responsiveness and reliability in remote driving scenarios.

Original language	English
Title of host publication	IEEE INFOCOM 2026 - IEEE Conference on Computer Communications
Publisher	IEEE
Pages	1888-1889
Number of pages	2
ISBN (Electronic)	979-8-3315-4961-9
ISBN (Print)	979-8-3315-4962-6
DOIs	https://doi.org/10.1109/INFOCOM59046.2026.11571175
Publication status	Published - 2026
Event	IEEE INFOCOM 2026 - Tokyo, Japan Duration: 18 May 2026 → 21 May 2026 https://infocom2026.ieee-infocom.org/

Publication series

Name	IEEE INFOCOM 2026 - IEEE Conference on Computer Communications
Publisher	IEEE
ISSN (Print)	0743-166X
ISSN (Electronic)	2641-9874

Conference

Conference	IEEE INFOCOM 2026
Country/Territory	Japan
City	Tokyo
Period	18/05/26 → 21/05/26
Internet address	https://infocom2026.ieee-infocom.org/

Bibliographical note

© 2026 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

This document is the author’s post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

Funding

This work was supported in part by the Japan Science and Technology Agency (JST) through the ASPIRE Program under Grant JPMJAP2325; and in part by Collaborative Research with Toyota Motor Corporation, Japan.

Funders	Funder number
Toyota Motor Corporation
Japan Science and Technology Agency	JPMJAP2325

Keywords

Semantic communication
Remote driving
Real-time video transmission

Access to Document

10.1109/INFOCOM59046.2026.11571175

Djahel2026AAMAccepted author manuscript, 3.93 MB

Cite this

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title = "Real-Time Semantic Communication System for Remote Driving",

abstract = "This paper introduces a real-time semantic communication system for remote driving, addressing the challenges of video transmission over constrained and fluctuating wireless communication links. Instead of transmitting raw video streams, the proposed system extracts and transmits compact semantic representations, significantly reducing bandwidth requirements while preserving task-relevant visual information. An end-to end semantic encoding-decoding pipeline enables low latency operator-view reconstruction with low latency, improving robustness without relying on high-throughput links. Implemented and evaluated on the real-time prototype, the proposed system demonstrates the practicality of semantic communication for enhancing responsiveness and reliability in remote driving scenarios.",

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Real-Time Semantic Communication System for Remote Driving

Abstract

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Bibliographical note

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Keywords

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