Modeling tagged pedestrian motion: A mean-field type game approach

被引：14

作者：

Aurell, Alexander ^{[1
]}

Djehiche, Boualem ^{[1
]}

机构：

[1] KTH Royal Inst Technol, Dept Math, S-10044 Stockholm, Sweden

来源：

TRANSPORTATION RESEARCH PART B-METHODOLOGICAL | 2019年 / 121卷

基金：

瑞典研究理事会;

关键词：

Pedestrian dynamics; Backward-forward stochastic differential equations; Mean-field type games; Congestion; Crowd aversion; Evacuation planning; STOCHASTIC DIFFERENTIAL-EQUATIONS; MAXIMUM PRINCIPLE; AVERSION; FLOW;

D O I：

10.1016/j.trb.2019.01.011

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper suggests a model for the motion of tagged pedestrians: Pedestrians moving towards a specified targeted destination, which they are forced to reach. It aims to be a decision-making tool for the positioning of fire fighters, security personnel and other services in a pedestrian environment. Taking interaction with the surrounding crowd into account leads to a differential nonzero-sum game model where the tagged pedestrians compete with the surrounding crowd of ordinary pedestrians. When deciding how to act, pedestrians consider crowd distribution-dependent effects, like congestion and crowd aversion. Including such effects in the parameters of the game, makes it a mean-field type game. The equilibrium control is characterized, and special cases are discussed. Behavior in the model is studied by numerical simulations. (C) 2019 Elsevier Ltd. All rights reserved.

引用

页码：168 / 183

页数：16

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