Crowd Dynamics: Modeling and Control of Multiagent Systems

Annual Review of Control Robotics and Autonomous Systems, vol. 6, pp. 261–282

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.

Authors 4

1. Xiaoqian Gong

   Arizona State University

   Affiliation as printed

   School of Mathematical and Statistical Sciences, Arizona State University, Tempe, Arizona, USA;

2. Michaël Herty Aachen Department of Mathematics

   RWTH Aachen University

   Affiliation as printed

   Department of Mathematics, RWTH Aachen University, Aachen, Germany;

3. Benedetto Piccoli

   Rutgers, The State University of New Jersey

   Affiliation as printed

   Department of Mathematical Sciences, Rutgers University–Camden, Camden, New Jersey, USA;

   Department of Mathematical Sciences, Rutgers University-Camden, Camden, New Jersey, USA;

4. Giuseppe Visconti

   Sapienza University of Rome

   Affiliation as printed

   Department of Mathematics, Sapienza University of Rome, Rome, Italy;