智能汽车多源融合环境感知系统综述  

Overview on Multi-Source Fusion Environment Perception System for Intelligent Vehicles

作　　者：李周达 查云飞 Li Zhouda;Zha Yunfei(Fujian University of Technology,Fuzhou 350108)

机构地区：[1]福建理工大学,福州350108

出　　处：《汽车文摘》2025年第4期1-11,共11页Automotive Digest

摘　　要：为了系统总结智能汽车多源融合环境感知技术的研究现状,对比分析了摄像头、激光雷达、毫米波雷达等传感器的原理与特性,综述了基于单传感器(如相机目标检测、激光雷达点云处理)及多传感器融合(数据层、特征层、决策层)的环境感知技术,分析了其技术瓶颈与挑战,并结合典型算法案例探讨其应用效果。研究表明:单一传感器存在固有局限性,如相机依赖光照条件、激光雷达成本高昂且无法获取语义信息;多传感器融合技术通过互补优势显著提升环境感知的鲁棒性,但数据异构性、实时性不足等问题仍需突破。为了应对复杂场景下的感知需求,智能化多模态融合算法、高性价比传感器集成及V2X协同感知技术是未来重点发展方向。To systematically summarize the research status of multi-source fusion environmental perception technology for intelligent vehicles,this paper compares and analyzes the principles and characteristics of various sensors including cameras,Light Detection and Ranging(LiDAR),and millimeter-wave radar.The environmental perception technologies based on single-sensor approaches(such as camera-based object detection and LiDAR point cloud processing)and multi-sensor fusion strategies(data-level,feature-level,and decision-level)are reviewed with their technical bottlenecks and challenges.Typical algorithm cases are also discussed to explore their application effectiveness.The research findings indicate that:single sensors exhibit inherent limitations,such as cameras’dependency on illumination conditions and LiDAR’s high cost with insufficient semantic information acquisition capability,as well as multi-sensor fusion technology significantly enhances environmental perception robustness through complementary advantages,yet challenges like data heterogeneity and insufficient real-time performance still remain unresolved.To meet the perception demands of complex scenarios,future development will focus on intelligent multi-modal fusion algorithms,cost-effective sensor integration,and V2X collaborative perception technologies.

关 键 词：智能汽车 环境感知 多传感器融合 相机 激光雷达 

分 类 号：U463.6[机械工程—车辆工程] TP212[交通运输工程—载运工具运用工程]