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On a mean field game optimal control approach modeling fast exit scenarios in human crowds

机译:在平均现场游戏最优控制方法上,模拟人群中的快速退出场景

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The understanding of fast exit and evacuation situations in crowd motion research has received a lot of scientific interest in the last decades. Security issues in larger facilities, like shopping malls, sports centers, or festivals necessitate a better understanding of the major driving forces in crowd dynamics. In this paper we present an optimal control approach modeling fast exit scenarios in pedestrian crowds. The model is formulated in the framework of mean field games and based on a parabolic optimal control problem. We consider the case of a large human crowd trying to exit a room as fast as possible. The motion of every pedestrian is determined by minimizing a cost functional, which depends on his/her position and velocity, the overall density of people, and the time to exit. This microscopic setup leads in a mean-field formulation to a nonlinear macroscopic optimal control problem, which raises challenging questions for the analysis and numerical simulations. We discuss different aspects of the mathematical modeling and illustrate them with various computational results.
机译:在过去的几十年中,对人群运动研究中对快速离开和撤离情况的理解引起了很多科学兴趣。大型设施(例如购物中心,体育中心或节日)中的安全问题需要更好地了解人群动态的主要驱动力。在本文中,我们提出了一种对行人拥挤的快速出口场景进行建模的最优控制方法。该模型是在平均场博弈的框架内并基于抛物线最优控制问题制定的。我们考虑到大量人群试图尽快离开房间的情况。每个行人的运动是通过最小化成本函数来确定的,成本函数取决于他/她的位置和速度,人员的总体密度以及离开的时间。这种微观设置导致平均场公式化导致非线性宏观最优控制问题,这为分析和数值模拟提出了具有挑战性的问题。我们讨论了数学建模的不同方面,并用各种计算结果进行了说明。

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