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首页> 外文期刊>Transportation Research Part B: Methodological >Real-time freeway traffic state estimation based on extended Kalman filter: a general approach
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Real-time freeway traffic state estimation based on extended Kalman filter: a general approach

机译：基于扩展卡尔曼滤波器的高速公路实时交通状态估计：通用方法

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摘要

A general approach to the real-time estimation of the complete traffic state in freeway stretches is developed based on the extended Kalman filter. First, a general stochastic macroscopic traffic flow model of freeway stretches is presented, while some simple formulae are proposed to model real-time traffic measurements. Second, the macroscopic traffic flow model along with the measurement model is organized in a compact state-space form, based on which a traffic state estimator is designed by use of the extended-Kalman-filtering method. While constructing the traffic state estimator, special attention is paid to the handling of the boundary conditions and unknown parameters of the macroscopic traffic flow model. A number of simulations are conducted to test the designed traffic state estimator under various traffic situations in a freeway stretch with on/off-ramps and a long inter-detector distance. Some key issues are carefully investigated, including tracking capability of the traffic state estimator, comparison of various estimation schemes, evaluation of different detector configurations, significance of the on-line model parameter estimation, sensitivity of the traffic state estimator to the initial values of the estimated model parameters and to the related standard deviation values, and dynamic tracking of time-varying model parameters. The achieved simulation results are very promising for the subsequent development and testing work that is briefly outlined.
机译：基于扩展卡尔曼滤波器，开发了一种实时估算高速公路路段完整交通状态的通用方法。首先，提出了高速公路路段的一般随机宏观交通流模型，并提出了一些简单的公式来对实时交通量测进行建模。其次，将宏观交通流模型与测量模型一起组织成紧凑的状态空间形式，在此基础上，使用扩展的卡尔曼滤波方法来设计交通状态估计器。在构造交通状态估算器时，应特别注意宏观交通流模型的边界条件和未知参数的处理。在开/关坡道和较长的检测器间距离的高速公路段上，进行了许多模拟，以测试各种交通状况下设计的交通状态估算器。仔细研究了一些关键问题，包括交通状态估算器的跟踪能力，各种估算方案的比较，不同检测器配置的评估，在线模型参数估算的重要性，交通状态估算器对交通状态初始值的敏感性估计模型参数以及相关的标准偏差值，并动态跟踪时变模型参数。所获得的仿真结果对于随后概述的后续开发和测试工作非常有希望。

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