Understanding step synchronization in social groups: A novel method to recognize group

Weisong Liu, Jun Zhang, Abdul Rahim Rasa, Xudong Li, Xiangxia Ren and Weiguo Song

Physica A: Statistical Mechanics and its Applications, 2023, vol. 628, issue C

Abstract: This study investigates the impact of social groups on the movement characteristics of pedestrian crowds. Through field observations and laboratory experiments, we observed step synchronization in social groups. To identify these groups, we developed a synchronization-based group recognition algorithm that leverages the trajectories of pedestrian heads during movement for the first time. By considering the distance, speed, and moving direction, our algorithm can detect social groups in crowds more accurately. Further, experimental tests with dyads and triples were conducted to evaluate the effectiveness and robustness of the algorithm. It is shown that the algorithm is able to calculate the synchronization ratios of pedestrians belonging to same social groups with a high degree of accuracy, ranging from 64% to 100%, which is significantly higher than those in other pedestrian combinations which ranged from 12% to 44%. Our findings demonstrate that the algorithm is capable of accurately distinguishing social groups within crowds.

Keywords: Social group; Step synchronization; Synchronization-based group recognition (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:628:y:2023:i:c:s0378437123007264

DOI: 10.1016/j.physa.2023.129171

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