How Social Attributes Affect the Movement Process of Subgroups When Facing a Static Obstacle

With the increasing number of studies on crowd behavior analysis, there has been a widespread interest in treating subgroups as an important topic. A previous experimental study has investigated the decision-making and motion behavior of subgroups when facing a static obstacle during movement. However, it is hard to quantify social attributes (e.g., interpersonal relationships and sense of identity) and little is known about how they affect the movement process of subgroups. Here, we propose a vision-driven model to solve this problem, in which two key model parameters are defined to control the spatial cohesion and attraction intensity, respectively. Numerical simulations demonstrate that the optimal regions of model parameters vary depending on different conditions of the three control variables (obstacle width, time pressure, and subgroup size). The spatial cohesion and attraction intensity barely change the movement process of subgroups in the maintaining state but significantly affect it in the splitting-merging state. This model can reproduce the herding effect of subgroup members in the merging process, which is affected to varying degrees by the modulation of model parameters. Overall, this work contributes to the simulation of subgroup behaviors from a sociopsychological perspective.

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Publication Details

Journal
IEEE Transactions on Computational Social Systems
Published
2024-11-19
DOI
https://doi.org/10.1109/tcss.2024.3493954
Primary Topic
Action Observation and Synchronization
Type
article
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article

How Social Attributes Affect the Movement Process of Subgroups When Facing a Static Obstacle

Wenfeng Yi, Erhui Wang, Wenhan Wu, Xiaoping Zheng et al.
IEEE Transactions on Computational Social Systems
Action Observation and Synchronization
article

How Social Attributes Affect the Movement Process of Subgroups When Facing a Static Obstacle

Wenfeng Yi, Erhui Wang, Wenhan Wu, Xiaoping Zheng, Xiaolu Wang
article en

Abstract

With the increasing number of studies on crowd behavior analysis, there has been a widespread interest in treating subgroups as an important topic. A previous experimental study has investigated the decision-making and motion behavior of subgroups when facing a static obstacle during movement. However, it is hard to quantify social attributes (e.g., interpersonal relationships and sense of identity) and little is known about how they affect the movement process of subgroups. Here, we propose a vision-driven model to solve this problem, in which two key model parameters are defined to control the spatial cohesion and attraction intensity, respectively. Numerical simulations demonstrate that the optimal regions of model parameters vary depending on different conditions of the three control variables (obstacle width, time pressure, and subgroup size). The spatial cohesion and attraction intensity barely change the movement process of subgroups in the maintaining state but significantly affect it in the splitting-merging state. This model can reproduce the herding effect of subgroup members in the merging process, which is affected to varying degrees by the modulation of model parameters. Overall, this work contributes to the simulation of subgroup behaviors from a sociopsychological perspective.

IEEE Transactions on Computational Social SystemsVol. 12(2)
Tsinghua University (CN)
Reduced inequalities
Openalex Percentile: Top 73%
Action Observation and Synchronization
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