网络化动态调控下城市路网交通拥堵控制技术综述

Control technology review of traffic congestion in urban road network under networked dynamic scheduling and control

以网络化动态链接交通装备下的城市交通安全监控为应用背景,从路网交通安全性能评估的可靠性评价指标和评价方法出发,分析了城市路网交通拥堵控制技术的国内外研究现状,指出了路网交通拥堵控制技术研究存在的问题和进一步研究方向。分析结果表明:由于网络化动态调控下交通信息资源存在传输时延、数据丢包与数据异常等缺陷,当前路网交通拥堵控制技术存在整体协调能力不强、多维动态模式研究欠缺以及出行者与交通系统之间的协调控制能力偏弱等缺陷;通过网络链接动态调配资源,实现路网交通拥堵状态下的联动控制,不仅需要考虑传统的交通畅通因素,还需要综合考虑信息传输机制、信道容量大小等与信息资源密切相关的因素;提出路网拥堵控制的关键子模型,并集成子模型构建了一种基于模型化方法的路网交通拥堵控制技术体系框架,框架的核心是交通数据库的建设;城市路网交通拥堵的分布式智能控制方法、自适应智能控制方法与集成型智能控制方法是未来重点关注的研究方向。

With the application of urban traffic security supervision under networked dynamic-link transportation equipment, the present domestic and overseas researches of traffic congestion control technology for urban road network were summarized based on the road network traffic safety performances including reliability evaluation indexes and evaluation methods. The problems and further development of recent researches were pointed. Analysis result shows that because of transmitting delay, data packet loss, and data exception of traffic information in networked dynamic scheduling and control, the traditional traffic congestion control technologies and methods of road network have the lack of global coordination ability, multi-dimension dynamic mode, and coordination ability between traveler and traffic performance. The arrangement of networked dynamic-link resource can be used for the implementation of linkage control at traffic congestion status, but the traditional factors for unimpeded transportation andthe factors relating to information resources, such as information transmitting mechanism and channel capacity etc. , have to be comprehensively considered. The key sub-control models for the traffic congestion control of road network are proposed. These sub-models are further integrated to establish a systematic-model based on the framework of traffic congestion control technology. It is pointed out that the core content of the model-based frame is the construction of traffic sate database. The future development trend and research focus of traffic congestion control technology are distributed intelligent control, adaptive intelligent control, and integrated intelligent control. 1 fig, 61 refs.