面向车联网的多模态感知识别与通信优化技术研究  

Research on Multi-Modal Sensing Recognition and Communication Optimization Technology for Vehicle Networking

作　　者：樊鹏程 FAN Pengcheng(China Post Construction Technology Limited Company,Nanjing 210012,China)

机构地区：[1]中邮建技术有限公司,江苏南京210012

出　　处：《通信电源技术》2025年第2期37-39,共3页Telecom Power Technology

摘　　要：车联网技术的发展对多模态感知识别与通信优化提出了更高要求。多模态感知识别通过融合多种数据源,高精度感知复杂交通场景。为保证实时数据传输和协同处理的有效性,车联网通信需要在多场景下满足低延迟、高可靠性的要求。就车联网通信在多场景需求下的优化进行探讨,分析多模态感知识别的关键技术和优化方法,提出感知与沟通协同优化的技术实现,以期为今后的智能网联汽车技术提供参考。The development of vehicle networking technology puts forward higher requirements for multi-mode perception recognition and communication optimization.Multi-modal perception and recognition can realize highprecision perception of complex traffic scenes by integrating multiple data sources.In order to ensure the effectiveness of real-time data transmission and collaborative processing,vehicle networking communication needs to meet the requirements of low latency and high reliability in multiple scenarios.This paper discusses the optimization of vehicleconnected communication under the requirements of multiple scenarios,discusses the key technologies and optimization methods of multi-mode perception and recognition,and puts forward the technical realization of collaborative optimization of perception and communication,in order to provide reference for future intelligent connected vehicle technology.

关 键 词：车联网 多模态感知 深度学习 通信优化 边缘计算 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] U495[自动化与计算机技术—计算机科学与技术]