arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1408.2177cond-mat.stat-mech
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行人动力学背景下自驱动两种群物体的随机模型

Stochastic model of self-driven two-species objects in the context of the pedestrian dynamics

Roberto da Silva, Agenor Hentz, Alexandre Alves

摘要:

在这项工作中,我们提出了一个模型来描述的统计波动的自驱动对象(物种A)走在对面的人群(物种B),以模拟制度的特点是走走停停波的背景下,行人动力学。通过使用单偏随机游动(SBRW)的概念,这种设置是通过偏微分方程和蒙特卡罗模拟建模。问题是非相互作用的,直到相反的粒子访问所考虑的粒子的相同单元。在这种情况下,每个单元的颗粒停留时间的延迟取决于相反物质的颗粒的浓度。我们分析了颗粒位置的波动,我们的结果表明,长尾和不对称分布的特点是更好地拟合一些色谱分布在文献中发现的非规则扩散。我们还表明,反向拥挤粒子的影响是能够扩大的目标粒子的分散有关的非偏置的情况下($α=0$)后,观察到这种分散的一个小的减少

英文摘要:

In this work we propose a model to describe the statistical fluctuations of the self-driven objects (species A) walking against an opposite crowd (species B) in order to simulate the regime characterized by stop-and-go waves in the context of pedestrian dynamics. By using the concept of single-biased random walks (SBRW), this setup is modeled both via partial differential equations and by Monte-Carlo simulations. The problem is non-interacting until the opposite particles visit the same cell of the considered particle. In this situation, delays on the residence time of the particles per cell depends on the concentration of particles of opposite species. We analyzed the fluctuations on the position of particles and our results show a non-regular diffusion characterized by long-tailed and asymmetric distributions which is better fitted by some chromatograph distributions found in the literature. We also show that effects of the reverse crowd particles is able to enlarge the dispersion of target particles in relation to the non-biased case ($α=0$) after observing a small decrease of this dispersion

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。

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