城市快速路交通态势评估理论与方法研究
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摘要
随着城市规模的不断扩大,快速路已成为支撑整个道路交通系统运转的关键,发挥着不可替代的作用。尽管快速路的定位是为长距离、快速交通出行服务,但日益增长的交通压力所带来的交通拥堵问题却也不可避免的发生在快速路上。正是由于相对封闭的道路结构,阻碍了排队车辆的疏散,导致快速路交通拥堵时空影响更加明显。由于快速路的重要功能和特殊地位,控制和解决城市快速路交通拥堵问题迫在眉睫。基于现有的交通数据和信息资源,如何快速捕捉交通运行的外在特征和演变规律,准确评判快速路网的交通现状及潜在能力,合理预测交通拥堵的变化和发展趋势,是快速路交通管理的关键。
因此,论文立足于为交通管理体系服务,从北京市快速路的实际问题和需求出发,开展对交通态势评估的关键理论和技术方法研究,重在突出城市快速路交通流的宏观特征和动态变化。
为全面了解快速路交通特性,基于实测数据标定了交通流基本图模型,对比分析了流量、占有率的时变关系和周期性特征；通过时间比例筛选,获取了高峰时段快速路网中的常发性拥堵路段,分析了典型路段的拥堵时空比例分布；引入残存函数并采用Lognormal概率分布描述了快速路段常发性交通拥堵持续时间特征；采用速度时空分布云图直观呈现了偶发事件下的交通拥堵演变规律。
为实现对快速路网交通拥堵状态的预报和预警,提出了基于改进元胞传输模型的快速路交通状态估计和预测模型。基于快速路物理结构和交通特点,引入可变元胞长度变量进行了不等长元胞划分,提出了“虚拟传输能力”概念适度扩大了元胞传输的时间间隔,并采用Van Aerde交通流模型替代假设的“梯形”结构模型,描述了交通流参数间的非线性关系；基于改进元胞传输模型获得交通流基本参数,设计了对交通拥堵强度、扩散范围、持续时间和影响程度的参数估计算法；选取密度为状态变量、速度为观测变量,建立了快速路非线性交通状态空间预测模型；引入了扩展卡尔曼滤波理论解决了非线性模型的多步预测问题；并最终通过了模型的实例验证。
围绕快速路宏观交通状态评价问题,构建了基于运行速度里程分布的“宏观交通状态指数”评价模型。提出了交通流宏观基本图模型的矢量算法,建立了北京市不同时期的快速路平均流量-平均密度-平均速度的关系基本图,用于描述网络实际交通服务水平；在此基础上,提出了快速路宏观交通状态的五级划分方法；经过大量统计分析得到了不同宏观交通状态下的运行速度概率分布模型,建立了基于百分位速度临界值的快速路“宏观交通状态指数”评价方法,并通过西三环路实例验证了模型的适用性。
最后,选取北京市西三环快速路网为研究对象,实现了交通状态多步预测；同时对路网宏观交通状态进行了预评价。
论文从北京市快速路交通问题的实际出发,完成了从理论分析、特征研究、模型构建到模型应用四个环节研究工作,同时从提高模型精度、扩大模型应用等方面提出了展望,以期能够为城市交通管理提供可靠的交通态势评估结果。
With the continued expansion of urban scale, expressways have become key factors that support the entire urban road traffic running, playing an irreplaceable role in urban transportation systems. Although the function of expressways is positioned to serve the long-distance and high-speed traffic, congestions caused by the increasing traffic demand inevitably happen on expressways. The relatively closed structure of the expressway network blocks the release of jammed traffic, resulting in more apparent effect of congestions in both temporal and spacialdimensions. Due to the important function and position of expressways, controlling and solving the congestion problems on the expressway network has become particularly urgent. Based on the available traffic data resources, the keys to the traffic managements on experessways are to quickly capture the external characteristics and evolutions of traffic, to accurately evaluate the traffic condition and potential capacity, and to reasonably predict the developing trend of congestions.
In this context, this dissertation is intended to study key theories and technologies, by responding to practical problems and needs of the expressway network in Beijing, attempting to support traffic management and controls, with an emphasis on the macroscopic characteristics and dynamic evolution of the traffic stream on expressways,
In order to completely understand the traffic characteristics on expressway networks, the traffic stream relationship model for expressways is calibrated based on the actual data; the time-varying correlation between traffic flow and occupancy and their periodic feature on different workdays are comparatively analyzed. Then, the recurrent severely congested segments on expressway networks during the peak hours are obtained using the method of time rate screening, and the temporal-spatial congested rate on typical expressway links is analyzed. The survival function and Lognormal distribution function are introduced to analyze the duration distribution characteristics of recurrent congestions, and the temporal-spatial speed distribution charts are used to visually show the evolution of traffic congestions.
In order to realize the forecasting and early warning of congestions on expressways, the traffic estimation and prediction model of the traffic evolution on expressways is developed based on the modified cell transmission model. Based on the network structure and traffic characteristics of expressways, the links are divided into cells of different lengths by introducing the parameter of variable cell length. The time interval of the clock update is expanded properly by proposing the concept of "virtual transmission capacity." Van Aerde traffic stream model, instead of the trapezoid model, is used to describe the non-linear relationship among traffic variables. Algorithms for estimating variables of the congestion intensity, breadth, duration, and extent are designed based on the basic traffic flow parameters deriving the modified cell transmission model. The nonlinear traffic state-spacial prediction model is developed for expressway networks by setting the traffic density as the state variable and the speed as the observational variable. In order to solve the nonlinear traffic model, the extended Kalman Filter is introduced to realize the state estimation and multistep prediction.
In regards to the evaluation problems of macroscopic traffic conditions on expressway networks, the evaluation model of "Macroscopic Traffic Condition Indices (MTCI)" is developed based on the mileage distribution of travel speeds on the network. The vector algorithm is proposed to obtain the macroscopic fundamental diagram model of networks, and the relationship models between average flow, average density, and average speed are built at different times, to represent the actual traffic service level. Based on the macroscopic fundamental diagram, the macroscopic traffic conditions on expressways are divided into five levels. The distribution model of travel speeds under different network conditions is built after numerous statistical analyses, the evaluation method of MTCI is developed based on the percentile thresholds, which is tested and verified using the western3rd ring-road expressway network.
Finally, the western3rd ring-road expressway network is selected to implement the traffic state multistep prediction. And then, the whole performance of the network is evaluated using the proposed evaluation model.
From the practical traffic problems on the expressway network in Beijing, this dissertation completes four steps of theory analysis, feature study, model development, and model application. It also presents some recommendations on improving the model accuracy, expanding model applications, and others for further study, in order to support and serve the urban traffic managements using the reliable traffic situation assessment results.
因此,论文立足于为交通管理体系服务,从北京市快速路的实际问题和需求出发,开展对交通态势评估的关键理论和技术方法研究,重在突出城市快速路交通流的宏观特征和动态变化。
为全面了解快速路交通特性,基于实测数据标定了交通流基本图模型,对比分析了流量、占有率的时变关系和周期性特征；通过时间比例筛选,获取了高峰时段快速路网中的常发性拥堵路段,分析了典型路段的拥堵时空比例分布；引入残存函数并采用Lognormal概率分布描述了快速路段常发性交通拥堵持续时间特征；采用速度时空分布云图直观呈现了偶发事件下的交通拥堵演变规律。
为实现对快速路网交通拥堵状态的预报和预警,提出了基于改进元胞传输模型的快速路交通状态估计和预测模型。基于快速路物理结构和交通特点,引入可变元胞长度变量进行了不等长元胞划分,提出了“虚拟传输能力”概念适度扩大了元胞传输的时间间隔,并采用Van Aerde交通流模型替代假设的“梯形”结构模型,描述了交通流参数间的非线性关系；基于改进元胞传输模型获得交通流基本参数,设计了对交通拥堵强度、扩散范围、持续时间和影响程度的参数估计算法；选取密度为状态变量、速度为观测变量,建立了快速路非线性交通状态空间预测模型；引入了扩展卡尔曼滤波理论解决了非线性模型的多步预测问题；并最终通过了模型的实例验证。
围绕快速路宏观交通状态评价问题,构建了基于运行速度里程分布的“宏观交通状态指数”评价模型。提出了交通流宏观基本图模型的矢量算法,建立了北京市不同时期的快速路平均流量-平均密度-平均速度的关系基本图,用于描述网络实际交通服务水平；在此基础上,提出了快速路宏观交通状态的五级划分方法；经过大量统计分析得到了不同宏观交通状态下的运行速度概率分布模型,建立了基于百分位速度临界值的快速路“宏观交通状态指数”评价方法,并通过西三环路实例验证了模型的适用性。
最后,选取北京市西三环快速路网为研究对象,实现了交通状态多步预测；同时对路网宏观交通状态进行了预评价。
论文从北京市快速路交通问题的实际出发,完成了从理论分析、特征研究、模型构建到模型应用四个环节研究工作,同时从提高模型精度、扩大模型应用等方面提出了展望,以期能够为城市交通管理提供可靠的交通态势评估结果。
With the continued expansion of urban scale, expressways have become key factors that support the entire urban road traffic running, playing an irreplaceable role in urban transportation systems. Although the function of expressways is positioned to serve the long-distance and high-speed traffic, congestions caused by the increasing traffic demand inevitably happen on expressways. The relatively closed structure of the expressway network blocks the release of jammed traffic, resulting in more apparent effect of congestions in both temporal and spacialdimensions. Due to the important function and position of expressways, controlling and solving the congestion problems on the expressway network has become particularly urgent. Based on the available traffic data resources, the keys to the traffic managements on experessways are to quickly capture the external characteristics and evolutions of traffic, to accurately evaluate the traffic condition and potential capacity, and to reasonably predict the developing trend of congestions.
In this context, this dissertation is intended to study key theories and technologies, by responding to practical problems and needs of the expressway network in Beijing, attempting to support traffic management and controls, with an emphasis on the macroscopic characteristics and dynamic evolution of the traffic stream on expressways,
In order to completely understand the traffic characteristics on expressway networks, the traffic stream relationship model for expressways is calibrated based on the actual data; the time-varying correlation between traffic flow and occupancy and their periodic feature on different workdays are comparatively analyzed. Then, the recurrent severely congested segments on expressway networks during the peak hours are obtained using the method of time rate screening, and the temporal-spatial congested rate on typical expressway links is analyzed. The survival function and Lognormal distribution function are introduced to analyze the duration distribution characteristics of recurrent congestions, and the temporal-spatial speed distribution charts are used to visually show the evolution of traffic congestions.
In order to realize the forecasting and early warning of congestions on expressways, the traffic estimation and prediction model of the traffic evolution on expressways is developed based on the modified cell transmission model. Based on the network structure and traffic characteristics of expressways, the links are divided into cells of different lengths by introducing the parameter of variable cell length. The time interval of the clock update is expanded properly by proposing the concept of "virtual transmission capacity." Van Aerde traffic stream model, instead of the trapezoid model, is used to describe the non-linear relationship among traffic variables. Algorithms for estimating variables of the congestion intensity, breadth, duration, and extent are designed based on the basic traffic flow parameters deriving the modified cell transmission model. The nonlinear traffic state-spacial prediction model is developed for expressway networks by setting the traffic density as the state variable and the speed as the observational variable. In order to solve the nonlinear traffic model, the extended Kalman Filter is introduced to realize the state estimation and multistep prediction.
In regards to the evaluation problems of macroscopic traffic conditions on expressway networks, the evaluation model of "Macroscopic Traffic Condition Indices (MTCI)" is developed based on the mileage distribution of travel speeds on the network. The vector algorithm is proposed to obtain the macroscopic fundamental diagram model of networks, and the relationship models between average flow, average density, and average speed are built at different times, to represent the actual traffic service level. Based on the macroscopic fundamental diagram, the macroscopic traffic conditions on expressways are divided into five levels. The distribution model of travel speeds under different network conditions is built after numerous statistical analyses, the evaluation method of MTCI is developed based on the percentile thresholds, which is tested and verified using the western3rd ring-road expressway network.
Finally, the western3rd ring-road expressway network is selected to implement the traffic state multistep prediction. And then, the whole performance of the network is evaluated using the proposed evaluation model.
From the practical traffic problems on the expressway network in Beijing, this dissertation completes four steps of theory analysis, feature study, model development, and model application. It also presents some recommendations on improving the model accuracy, expanding model applications, and others for further study, in order to support and serve the urban traffic managements using the reliable traffic situation assessment results.
引文
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