车联网 (IoV) 有望成为为联网车辆和用户提供高级服务的中央基础设施，以提高运输效率和安全。各种新兴应用/服务带来了对联网车辆和路边单元 (RSU) 之间移动数据流量的爆炸式增长需求，给车联网带来了频谱稀缺的重大挑战。在这篇文章中，我们提出了一种协作语义感知架构，将协作用户的基本语义传达给服务器，以减少数据流量。与当前主要基于在句法通信方面堆积高度复杂的信号处理技术和多路访问能力的解决方案相比，本文提出了车联网中语义感知内容交付的想法。具体来说，追求源数据基本语义的成功传输，而不是像传统句法通信那样准确接收符号而不管它们的含义。为了评估所提出架构的优势，我们提供了智能交通系统 (ITS) 中车辆图像检索任务的案例研究。仿真结. 为了评估所提出架构的优势，我们提供了智能交通系统 (ITS) 中车辆图像检索任务的案例研究。仿真结. 为了评估所提出架构的优势，我们提供了智能交通系统 (ITS) 中车辆图像检索任务的案例研究。仿真结.

　　"点击查看英文标题和摘要"

　　The Internet of Vehicles (IoV) is expected to become the central infrastructure to provide advanced services to connected vehicles and users for higher transportation efficiency and security. A variety of emerging applications/services bring explosively growing demands for mobile data traffic between connected vehicles and roadside units (RSUs), imposing the significant challenge of spectrum scarcity in the IoVPG电子麻将胡了2. In this article, we propose a cooperative semantic-aware architecture to convey essential semantics from collaborated users to servers for lessening data traffic. In contrast to current solutions that are mainly based on piling up highly complex signal processing techniques and multiple access capabilities in terms of syntactic communications, this article puts forth the idea of semantic-aware content delivery in the IoV. Specifically, the successful tranission of essential semantics of the source data is pursued rather than the accurate reception of symbols regardless of their meaning, as in conventional syntactic communications. To assess the benefits of the proposed architecture, we provide a case study of an image retrieval task for vehicles in intelligent transportation systems (ITSs). Simulation results demonstrate that the proposed architecture outperforms existing solutions, with fewer radio resources, especially in a low-signal-to-noise-ratio (SNR) regime, which can shed light on the potential of the proposed architecture in extending applications in extreme environments.