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Behavioural repertoires in moving crowds: an observational approach
Anna Sieben1,2, Tom Postmes3
1Forschungszentrum Jülich, Institute for Advanced Simulation (IAS-7), Jülich, Germany.
Royal Society Open Science
|February 20, 2025
Summary
Understanding crowd behavior is complex. This study introduces a systematic observational method to analyze pedestrian movement, revealing diverse behavioral repertoires and social unit engagements in crowd simulations.
Area of Science:
- Social Psychology
- Human Movement Behavior
- Crowd Dynamics
Background:
- Current crowd movement models struggle to capture the wide variety of observed crowd behaviors.
- Social psychological principles regarding social meaning and structure recognition are crucial for understanding human interaction in crowds.
Purpose of the Study:
- To develop a systematic observational approach for analyzing crowd movement behavior.
- To create a comprehensive ethogram of behavioral repertoires within pedestrian crowds.
- To inform the development of next-generation crowd movement models.
Main Methods:
- Conducted pedestrian crowd experiments with 351 participants across four runs, simulating a concert entry scenario.
- Utilized top-view video recordings and qualitative, iterative systematic observation to develop an ethogram.
- Enriched observational data with pedestrian trajectory data to generate density heatmaps, speed analyses, and time-distance plots.
Main Results:
- Identified a diverse range of behavioral repertoires within the crowd, performed by individuals, small interactive groups, and large action groups.
- Observed frequent and rapid shifts in participants' movement repertoires and social unit engagement.
- Analysis revealed variations in movement patterns influenced by motivation to reach the destination first.
Conclusions:
- The developed systematic observational approach provides a detailed framework for studying complex crowd behaviors.
- Findings highlight the dynamic nature of individual and group behavior within pedestrian crowds.
- This research contributes to a deeper understanding of social factors influencing crowd movement, aiding future model development.
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