Ye Sha, Wu Qiong, Fan Pingyi, Fan Qiang
School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China.
State Key Laboratory of Space Network and Communications, Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China.
Entropy (Basel). 2025 Apr 20;27(4):445. doi: 10.3390/e27040445.
The Internet of Vehicles (IoV), as the core of intelligent transportation system, enables comprehensive interconnection between vehicles and their surroundings through multiple communication modes, which is significant for autonomous driving and intelligent traffic management. However, with the emergence of new applications, traditional communication technologies face the problems of scarce spectrum resources and high latency. Semantic communication, which focuses on extracting, transmitting, and recovering some useful semantic information from messages, can reduce redundant data transmission, improve spectrum utilization, and provide innovative solutions to communication challenges in the IoV. This paper systematically reviews state-of-the-art semantic communications in the IoV, elaborates the technical background of the IoV and semantic communications, and deeply discusses key technologies of semantic communications in the IoV, including semantic information extraction, semantic communication architecture, resource allocation and management, and so on. Through specific case studies, it demonstrates that semantic communications can be effectively employed in the scenarios of traffic environment perception and understanding, intelligent driving decision support, IoV service optimization, and intelligent traffic management. Additionally, it analyzes the current challenges and future research directions. This survey reveals that semantic communications have broad application prospects in the IoV, but it is necessary to solve the real existing problems by combining advanced technologies to promote their wide application in the IoV and contributing to the development of intelligent transportation systems.
车联网（IoV）作为智能交通系统的核心，通过多种通信模式实现车辆与其周围环境的全面互联，这对自动驾驶和智能交通管理具有重要意义。然而，随着新应用的出现，传统通信技术面临频谱资源稀缺和高延迟等问题。语义通信专注于从消息中提取、传输和恢复一些有用的语义信息，能够减少冗余数据传输，提高频谱利用率，并为车联网中的通信挑战提供创新解决方案。本文系统地综述了车联网中最新的语义通信，阐述了车联网和语义通信的技术背景，并深入讨论了车联网中语义通信的关键技术，包括语义信息提取、语义通信架构、资源分配与管理等。通过具体案例研究，表明语义通信能够有效地应用于交通环境感知与理解、智能驾驶决策支持、车联网服务优化以及智能交通管理等场景。此外，分析了当前面临的挑战和未来的研究方向。这项综述表明，语义通信在车联网中具有广阔的应用前景，但有必要通过结合先进技术解决实际存在的问题，以促进其在车联网中的广泛应用，并为智能交通系统的发展做出贡献。
