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Traffic Density Modeling and Estimation on Stretched Highways: The Case for Lipschitz-Based Observers

机译:延伸公路上的交通密度建模和估计:基于Lipschitz的观察员的案例

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As an alternative to installing traffic sensors on all highway segments, traffic density estimation routines can be utilized to estimate traffic state on sensor-less segments. To that end, we first derive a generalized traffic flow model for stretched highways with arbitrary number and location of ramp flows. The flow model is based on the Lighthill-Whitham-Richards (LWR) model and Greenshield's fundamental diagram. This derived model is written as a nonlinear state-space system, making it amenable to control-theoretic formulations for nonlinear dynamic networks. We then show that the nonlinearities present in the derived models are locally Lipschitz continuous by providing analytical Lipschitz constants that depend on the network parameters and topology. The analytical derivation is then used to perform traffic density estimation given a limited number of traffic sensors using a vintage Lipschitz-based state estimator. This estimator design graciously scales to thousands of highway segments. Numerical tests are given providing early confidence in the potential of the proposed methods.
机译:作为在所有高速公路路段上安装交通传感器的替代方法,可以使用交通密度估算例程来估算无传感器路段上的交通状态。为此,我们首先导出具有任意数量和位置的匝道流量的拉伸高速公路的广义交通流模型。流量模型基于Lighthill-Whitham-Richards(LWR)模型和Greenshield的基本图。这个导出的模型被写为一个非线性状态空间系统,使得它可以适用于非线性动态网络的控制理论公式。然后,我们通过提供依赖于网络参数和拓扑的分析性Lipschitz常数,来表明存在于导出模型中的非线性是局部Lipschitz连续的。然后,使用基于老式Lipschitz的状态估算器,在使用有限数量的交通传感器的情况下,将分析推导用于执行交通密度估算。此估算器设计可扩展到数千个高速公路路段。给出的数值测试为所提出方法的潜力提供了早期的信心。

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