The prediction of the dynamic loads produced by groups of people is a crucial aspect of the design of stadiums or entertainment venues. This is because the coordinated motion of lively crowds may induce severe vibration levels in the structure, which can become critical for both human comfort and structural safety. However, the available information on this topic is very limited. Human loads often rely on deterministic models that do not consider the interaction and the coordination achieved by the participants or try to account for them through empirical assumptions. Therefore, they could find very little correspondence in realistic scenarios. This article aims to close this gap by introducing a vision-based technique able to directly measure crowd loading and quantify the synchronization level between individuals. Starting from a sequence of images of a jumping crowd, digital image correlation (DIC) is used to extract the vertical velocity of different regions occupied by the participants; then, the vertical force time record is estimated. Finally, the comparison between the actual force signals and their envelopes allows for estimating the crowd synchronization over time. The method has been successfully validated with two field tests on the grandstands of the Giuseppe Meazza stadium in Milan, demonstrating its ability to reliably estimate the synchronization level reached by the participants.

Vision-Based Method to Measure the Synchronization Level of Jumping Crowds

Turrisi S.;Zappa E.;Cigada A.
2023-01-01

Abstract

The prediction of the dynamic loads produced by groups of people is a crucial aspect of the design of stadiums or entertainment venues. This is because the coordinated motion of lively crowds may induce severe vibration levels in the structure, which can become critical for both human comfort and structural safety. However, the available information on this topic is very limited. Human loads often rely on deterministic models that do not consider the interaction and the coordination achieved by the participants or try to account for them through empirical assumptions. Therefore, they could find very little correspondence in realistic scenarios. This article aims to close this gap by introducing a vision-based technique able to directly measure crowd loading and quantify the synchronization level between individuals. Starting from a sequence of images of a jumping crowd, digital image correlation (DIC) is used to extract the vertical velocity of different regions occupied by the participants; then, the vertical force time record is estimated. Finally, the comparison between the actual force signals and their envelopes allows for estimating the crowd synchronization over time. The method has been successfully validated with two field tests on the grandstands of the Giuseppe Meazza stadium in Milan, demonstrating its ability to reliably estimate the synchronization level reached by the participants.
2023
Computer vision, crowd synchronization, digital image correlation (DIC), Structural Health Monitoring (SHM), vibration serviceability
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1262990
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