摘要
为提高公路隧道交通信息感知水平,实现公路隧道发展数字化、智能化运营管理需求,基于雷视融合感知技术,建立了公路隧道交通管控系统,通过时空匹配、ROI目标融合和距离融合方式依次实现雷视融合感知;构建了公路隧道交通管控系统体系架构,包括设备层、通信层、数据层、应用层和用户层5个层次;以雷视融合、数字孪生等关键技术驱动,建立了三维实景化管控、数据分析研判、应急联动管控和信息共享四大应用平台,实现了全息感知、多源融合、事件研判、辅助决策、智能控制、精细管理等功能。通过济莱高速公路隧道群实例证明:基于雷视融合的公路隧道交通管控系统可精准感知隧道运行状态,为公路隧道信息感知和智能化管控提供技术支撑。
In order to enhance the level of traffic information perception in highway tunnels and meet the needs of digital and intelligent development of highway tunnels,a traffic control system based on radar-video fusion perception technology has been established.This system realizes radar-video fusion perception by a process of spatiotemporal matching,ROI(Region of Interest)target fusion,and distance fusion.The system architecture comprises five layers:equipment,communication,data,application,and user.Driven by key technologies such as radar-video fusion and digital twin,four major application platforms have been established:3D real-world control,data analysis and judgement,emergency linkage control,and information sharing.These platforms enable functions such as holographic perception,multi-source fusion,event research and judgement,auxiliary decision-making,intelligent control,and fine management.An exemplar case of the Jilai Expressway tunnel group illustrates that the highway tunnel traffic control system,based on radar-video fusion,can precisely perceive tunnel operating conditions.Consequently,this system provides substantial technical support for information perception and intelligent management and control of highway tunnels.
作者
陈宏
付立家
尚康
朱香敏
CHEN Hong;FU Lijia;SHANG Kang;ZHU Xiangmin(Shandong Hi-speed Company Limited,Ji′nan,250014;China Merchants Chongqing Communications Technology Research&Design Institute Co.,Ltd.,Chongqing 400067;College of Transportation,Chongqing Jiaotong University,Chongqing 400074)
出处
《公路交通技术》
2023年第6期153-159,共7页
Technology of Highway and Transport
基金
交通运输行业重点科技项目(2021-MS6-145)
山东省交通运输厅科技计划项目(2021B61)。
关键词
公路隧道
交通管控系统
雷视融合
时空匹配
ROI目标融合
highway tunnels
traffic control system
radar-video fusion
spatiotemporal matching
ROI target fusion