Hydrodynamic traffic flow models including random accidents: A kinetic derivation

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Felisia Angela Chiarello, Simone Göttlich, Thomas Schillinger, Andrea Tosin
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引用次数: 0

Abstract

We present a formal kinetic derivation of a second order macroscopic traffic model from a stochastic particle model. The macroscopic model is given by a system of hyperbolic partial differential equations (PDEs) with a discontinuous flux function, in which the traffic density and the headway are the averaged quantities. A numerical study illustrates the performance of the second order model compared to the particle approach. We also analyse numerically uncertain traffic accidents by considering statistical measures of the solution to the PDEs.
包括随机事故在内的水动力交通流模型:动力学推导
我们从随机粒子模型出发,对二阶宏观交通模型进行了正式的动力学推导。宏观模型由一个双曲偏微分方程(PDE)系统给出,该系统具有不连续的流量函数,其中交通密度和车速是平均量。数值研究说明了二阶模型与粒子法相比的性能。我们还通过考虑 PDEs 解的统计量,对不确定的交通事故进行了数值分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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