research-article

A model for flexible representation of social groups in crowd simulation

Authors:

Joaquim Cavalcante-Neto,

Creto VidalAuthors Info & Claims

Volume 101, Issue C

Pages 7 - 22

https://doi.org/10.1016/j.cag.2021.08.005

Published: 01 December 2021 Publication History

Abstract

Taking into consideration the behavior of social groups, such as groups of friends, couples and families, is very important in crowd simulation. Existing approaches of group modeling offer little flexibility for customizing the structure of the groups and the relationships between their members, which limits their representation power. Often, those approaches also have limitations regarding their ability to represent groups of arbitrary sizes, as well as to represent certain aspects of the groups’ cohesion, such as the ability of modeling how their members will walk together and whether they will follow the same routes. This work proposes a way of modeling groups with different structures, in which roles of leadership can be assigned to some of their members. The approach can also represent groups of arbitrary sizes that may consist of subgroups, and treat different levels of relationships between their members. Moreover, the groups can be modeled in such a way that their members show either a strong cohesion with one another or a loose cohesion, in which the members behave more autonomously when dealing with collision avoidance and choice of routes. Nevertheless, the sense of group is always present as the model offers the ability of regrouping whenever one or more members of a group are left behind. The model also includes a new personality factor that represents the urge of the group members to move towards their destinations when they experience a strong impedance from the crowd. The approach is based on states that the pedestrians can assume based on their profiles and on the social forces model.

Graphical abstract

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Highlights

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Model capable of representing groups with flexible structures and relationships.

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Model with flexibility of group cohesion.

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New personality factor that represents a member’s urge to reach its goal.

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Cited By

Itatani RPelechano N(2024)Social Crowd Simulation: Improving Realism with Social Rules and Gaze BehaviorProceedings of the 17th ACM SIGGRAPH Conference on Motion, Interaction, and Games10.1145/3677388.3696337(1-11)Online publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1145/3677388.3696337
Ding HWang SXie ZLi MMa L(2023)A fine-grained vision and language representation framework with graph-based fashion semantic knowledgeComputers and Graphics10.1016/j.cag.2023.07.025115:C(216-225)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1016/j.cag.2023.07.025
Hu MCai W(2022)Analysis of Lifeboat Embarkation Efficiency for Cruise Passengers under Multiple ScenariosScientific Programming10.1155/2022/54916212022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/5491621
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Index Terms

A model for flexible representation of social groups in crowd simulation
1. Computing methodologies
  1. Computer graphics
    1. Animation
      1. Physical simulation
  2. Modeling and simulation
    1. Model development and analysis
    2. Simulation types and techniques
      1. Agent / discrete models

Index terms have been assigned to the content through auto-classification.

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Published In

cover image Computers and Graphics

Computers and Graphics Volume 101, Issue C

Dec 2021

106 pages

ISSN:0097-8493

Issue’s Table of Contents

Elsevier Ltd.

Publisher

Pergamon Press, Inc.

United States

Publication History

Published: 01 December 2021

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Cited By

Itatani RPelechano N(2024)Social Crowd Simulation: Improving Realism with Social Rules and Gaze BehaviorProceedings of the 17th ACM SIGGRAPH Conference on Motion, Interaction, and Games10.1145/3677388.3696337(1-11)Online publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1145/3677388.3696337
Ding HWang SXie ZLi MMa L(2023)A fine-grained vision and language representation framework with graph-based fashion semantic knowledgeComputers and Graphics10.1016/j.cag.2023.07.025115:C(216-225)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1016/j.cag.2023.07.025
Hu MCai W(2022)Analysis of Lifeboat Embarkation Efficiency for Cruise Passengers under Multiple ScenariosScientific Programming10.1155/2022/54916212022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/5491621
Jorge J(2022)EditorialComputers and Graphics10.1016/j.cag.2021.11.009101:C(1-2)Online publication date: 9-Apr-2022
https://dl.acm.org/doi/10.1016/j.cag.2021.11.009

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