Crowd Dynamics: Modeling and Control of Multiagent Systems

卷:6

Review

关键词: SELF-DRIVEN PARTICLES;    MEAN-FIELD CONTROL;    PREDICTIVE CONTROL;    FEEDBACK-CONTROL;    SPARSE STABILIZATION;    CONFLICT-RESOLUTION;    EMERGENT BEHAVIOR;    FLOCKING DYNAMICS;    CONTINUUM-LIMIT;    KINETIC-MODELS;   

DOI  :  10.1146/annurev-control-060822-123629

来源: SCIE

【 摘 要 】

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.

【 授权许可】

Free