人工智能赋能道路交通拥堵治理技术框架研究  

Framework of Road Traffic Congestion Governance Techniques Based on Artificial Intelligence

作　　者：张扬 ZHANG Yang(Shanghai Municipal Urban-rural Construction and Transportation Development Institute,Shanghai 200032,China)

机构地区：[1]上海市城乡建设和交通发展研究院,上海200032

出　　处：《交通与运输》2022年第4期47-51,共5页Traffic & Transportation

基　　金：上海市科委项目《交通拥堵预判与智能主动管控技术研究与示范》(19DZ1209000);上海市住建委科研项目《城区智慧建设运营管理技术与应用研究》(沪建科2021-002-027)。

摘　　要：城市道路交通治理一直是国内外各大城市亟待攻克的共性难题,如何从主动发现、自动识别、科学诊断、智能解决、反馈优化等方面入手,将人工智能深度融入城市交通拥堵治理场景,基于大数据、云计算和人工智能技术,提出人工智能赋能拥堵治理技术框架。围绕人工智能赋能交通拥堵研判与主动管控的全流程将其划分为全息感知数据融合、交通拥堵智能预判、智能主动管控、赋能应用示范等4个技术框架。通过构建科学合理的人工智能赋能道路交通拥堵治理技术框架,形成人工智能在交通拥堵治理的应用基础。Urban road traffic management has been a common problem to be solved in mega cities.Under the background of fast innovation development in artificial intelligence(AI),it is essential to take advantage of AI to promote urban traffic governance based on existing traffic big data.From the aspects of active finding,automatic recognition,scientific diagnosis,intelligent resolution and feedback optimization,the paper aims to provide a scientific AI+technique framework of road traffic congestion governance,which is the basis of AI+Transportation application.It also divides the framework into four ones including traffic data holographic perception and fusion,intelligent traffic congestion forecasts,intelligent active traffic management and control,and AI application demonstration.The novel framework research result is basic reference of AI’s application to traffic governance.

关 键 词：人工智能 智能交通系统 拥堵研判 主动管控 技术框架 

分 类 号：U491[交通运输工程—交通运输规划与管理]