arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1711.02424math.NAcs.NAmath.APnlin.AO
收藏

二维交通动力学的混合随机动力学描述

Hybrid stochastic kinetic description of two-dimensional traffic dynamics

RWTH Aachen University(亚琛工业大学);Politecnico di Torino(都灵理工大学)

Michael Herty, Andrea Tosin, Giuseppe Visconti, Mattia Zanella

AI总结:

本文提出了一种二维交通动力学模型,考虑了车辆在车道内交互和变道时的速度变化,通过混合随机福克-普朗克-波尔兹曼方程计算交通流的速度-密度图,并利用实数据验证了结果。

摘要:

在本文中,我们提出了一种二维交通动力学模型,考虑了车辆在车道内交互和变道时的速度变化。假设变道频率低于车道内交互频率,并考虑到其数学描述可以在某些模型参数的不确定性下进行。在准不变交互极限下,我们推导出一个混合随机福克-普朗克-波尔兹曼方程。通过适当的数值方法,即结构保持和直接蒙特卡罗方案,我们利用该方程计算交通流沿车道和跨车道的速度-密度图,包括数据分散性的估计,并将其与实际数据进行验证。

英文摘要:

In this work we present a two-dimensional kinetic traffic model which takes into account speed changes both when vehicles interact along the road lanes and when they change lane. Assuming that lane changes are less frequent than interactions along the same lane and considering that their mathematical description can be done up to some uncertainty in the model parameters, we derive a hybrid stochastic Fokker-Planck-Boltzmann equation in the quasi-invariant interaction limit. By means of suitable numerical methods, precisely structure preserving and direct Monte Carlo schemes, we use this equation to compute theoretical speed-density diagrams of traffic both along and across the lanes, including estimates of the data dispersion, and validate them against real data.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑