Due to different structures in administrative department and technical standard, the junction of freeway network and the urban road network becomes the bottleneck of traffic flow conversion in our country, and it always causes traffic congestions and accidents which have been obviously limited the efficiency of the road-network's operation. According to the complex problem with Chinese characteristics, the existing traffic management, control theory and methods cannot solve such problem effectively. For this reason, the research aims at researching cooperative control theory and methology of the junction of isomerism road network system. By integrating multiple disciplines, mythology and technology, based on the main-lane related ramp which is multi-sectional and multi-parameter, the research also establishes an evaluation index as well as an attribute definition standard. And then, the study makes a dynamic forecasting to junction of isomerism road network system by constructing Markov Chain-Monte Carlo. After that, a interactive collaborative model, controlling strategy and methology about the junction of isomerism road network system is proposed. The study can provide scientific theory and method in solving the traffic coordination controlling problem at the junction of freeway network and the urban road network which shows its prospect in application.
由于我国高速公路网与城市道路网的管理主体及技术标准的异构性,且缺乏协同控制,异构路网结合部成为路网的“瓶颈”,往往造成关联路网及路段的拥堵,严重制约着路网运行效率。对此带有中国特色的复杂系统问题,目前国内外尚缺乏针对性的研究成果,现有交通管理与控制理论方法也难以有效解决这类问题。为此,本项目以异构路网系统结合部协同控制理论方法研究为目标,通过多学科交叉、方法与技术集成,构建基于主线-关联匝道多断面、多参数的异构路网系统结合部交通状态评价指标,研究属性划分与界定方法,以及建立马尔科夫蒙特卡罗交通状态的预判模型;提出异构路网系统结合部交互式协同模式、控制策略与方法,运用优化控制理论方法,建立基于多智能体和分层递阶的动态多目标优化控制模型,以实现路网结合部的集成优化控制。本研究既可为解决我国高速公路与城市路网这种异构系统的结合部交通协同控制问题提供科学的理论依据,也有良好的应用前景。
由于管理主体及技术标准的异构,使得我国高速公路网与城市路网结合部交通流转换由于缺乏协同控制而成为瓶颈,往往造成关联路网及路段的拥堵和事故频发,严重制约着路网运行效率。本课题以异构路网系统结合部协同控制理论方法研究为目标,通过多学科交叉、方法与技术集成,构建基于主线-关联匝道多断面、多参数的异构路网系统结合部交通状态评价指标,研究属性划分与界定方法,以及建立基于马尔科夫蒙特卡罗交通状态的组合预判模型;提出异构路网系统结合部交互式协同模式、控制策略与方法,并建立分层递阶多智能体协同控制模型。本研究为解决我国高速公路与城市路网这种异构系统的结合部交通协同控制问题提供科学的理论依据,具有良好的应用前景。
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数据更新时间:2023-05-31
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