Crowd Dynamics: Modeling and Control of Multiagent Systems

IF 11.2 1区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Annual Review of Control Robotics and Autonomous Systems Pub Date : 2022-10-06 DOI:10.1146/annurev-control-060822-123629

Xiaoqian Gong, M. Herty, B. Piccoli, G. Visconti

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引用次数: 5

Abstract

This review aims to present recent developments in modeling and control of multiagent systems. A particular focus is set on crowd dynamics characterized by complex interactions among agents, also called social interactions, and large-scale systems. Specifically, in a crowd each individual agent interacts with a field generated by the other agents and the environment. These systems can be modeled at the microscopic scale by ordinary differential equations, while an alternative description at the mesoscopic scale is given by a partial differential equation for the propagation of the probability density of the agents. Control actions can be applied at the individual level as well as at the level of the corresponding fields. This article presents and compares different control types, and the specific application to multilane, multiclass traffic is developed in some detail, showing the main tools at work in a hybrid setting with relevant impacts on autonomous driving. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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群体动力学:多智能体系统的建模与控制

本文旨在介绍多智能体系统建模和控制方面的最新进展。特别关注的是群体动力学，其特征是代理人之间的复杂互动，也称为社会互动和大规模系统。具体来说，在人群中，每个个体智能体都与其他智能体和环境生成的域进行交互。这些系统可以通过常微分方程在微观尺度上建模，而在介观尺度上的另一种描述是由代理概率密度传播的偏微分方程给出的。控制动作既可以应用于个人级别，也可以应用于相应字段级别。本文介绍并比较了不同的控制类型，并详细介绍了在多车道、多类别交通中的具体应用，展示了在混合动力环境下工作的主要工具及其对自动驾驶的相关影响。预计《控制、机器人和自主系统年度评论》第14卷的最终在线出版日期是2023年5月。修订后的估计数请参阅http://www.annualreviews.org/page/journal/pubdates。

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

Annual Review of Control Robotics and Autonomous Systems Multiple-

CiteScore

28.30

自引率

2.20%

发文量

期刊介绍： The Annual Review of Control, Robotics, and Autonomous Systems offers comprehensive reviews on theoretical and applied developments influencing autonomous and semiautonomous systems engineering. Major areas covered include control, robotics, mechanics, optimization, communication, information theory, machine learning, computing, and signal processing. The journal extends its reach beyond engineering to intersect with fields like biology, neuroscience, and human behavioral sciences. The current volume has transitioned to open access through the Subscribe to Open program, with all articles published under a CC BY license.