一种速度数据同化的交通模型

D. Work, Sebastien Blandin, Olli-Pekka Tossavainen, B. Piccoli, A. Bayen
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引用次数: 262

摘要

本文的动机是公路交通的实际问题估计使用速度测量从启用GPS的移动设备,如手机。为了简化估计过程,建立了公路交通速度模型,得到了一个观测算子为线性的动态系统。本文在Lighthill-Whitham-Richards (LWR)密度偏微分方程的基础上,提出了一个新的高速公路交通速度演化的标量双曲偏微分方程(PDE)模型。对于二次通量函数,证明了新速度偏微分方程的解与LWR偏微分方程的解的等价性。由于这种等价性不适用于一般的通量函数,本文提出了一种基于Godunov格式的速度演化离散模型。通过对PDE的弱边界条件的显式实例化,将离散速度演化模型推广到网络中,从而使该模型适用于任意公路网。得到的速度模型是一个具有线性观测算子的非线性不可微离散时间动力系统,对其采用基于蒙特卡罗的集合卡尔曼滤波方法
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A traffic model for velocity data assimilation
This article is motivated by the practical problem of highway traffic estimation using velocity measurements from GPS enabled mobile devices such as cell phones. In order to simplify the estimation procedure, a velocity model for highway traffic is constructed, which results in a dynamical system in which the observation operator is linear. This article presents a new scalar hyperbolic partial differential equation (PDE) model for traffic velocity evolution on highways, based on the seminal Lighthill-Whitham-Richards (LWR) PDE for density. Equivalence of the solution of the new velocity PDE and the solution of the LWR PDE is shown for quadratic flux functions. Because this equivalence does not hold for general flux functions, a discretized model of velocity evolution based on the Godunov scheme applied to the LWR PDE is proposed. Using an explicit instantiation of the weak boundary conditions of the PDE, the discrete velocity evolution model is generalized to a network, thus making the model applicable to arbitrary highway networks. The resulting velocity model is a nonlinear and nondifferentiable discrete time dynamical system with a linear observation operator, for which a Monte Carlo based ensemble Kalman filtering data
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