摘要
理论导向型教学模式难以满足车路协同领域对于工程实践能力的培养需求,导致课程教学与智能交通行业发展需求存在显著差距。本研究系统构建路侧传感器的目标检测及跟踪、时空同步、多传感器融合、场景算法等核心理论体系,并搭建全栈式车路协同实验平台。通过开展基于该平台的实践教学,不仅能增加学生对车路协同相关理论的理解深度,同时也显著提升学生操作路侧传感器、边缘计算单元、路侧单元、车载单元的动手能力,为未来从事相关工程实践奠定坚实的基础。
Theory-oriented teaching modes fail to meet the engineering practice requirements for talent cultivation in this field,resulting in a substantial gap between curriculum design and industry demands in intelligent transportation.This research systematically constructs core theoretical frameworks including roadside sensor-based target detection/tracking,spatiotemporal synchronization,multi-sensor fusion,and scenario algorithms,while establishing a full-stack V2I experimental platform.By learning on this platform,students can gain a deeper understanding of the fundamental theories of V2I collaboration.At the same time,they can develop hands-on skills in operating roadside sensors,edge computing units,roadside units,and onboard units,thereby establishing a solid foundation for future engineering practices in this domain.
作者
魏吉敏
张长隆
戴金钢
瞿仕波
王泽涛
鲍海兴
熊威
WEI Jimin;ZHANG Changlong;DAI Jingang;QU Shibo;WANG Zetao;BAO Haixing;XIONG Wei(CiDi Inc.,Changsha 410208,China)
出处
《交通工程》
2025年第12期83-89,共7页
Journal of Transportation Engineering
基金
湖南省科技创新计划项目(2025RC5002)。
关键词
车路协同
多传感器融合
实验平台
边缘计算
vehicle-to-infrastructure
multi-sensor fusion
experimental platform
edge computing
