Discovering interaction mechanisms in crowds via deep generative surrogate experiments

Abstract Understanding pedestrian crowd dynamics is a fundamental challenge in active matter physics and crucial for efficient urban infrastructure design. Complexity emerges from social interactions, which are often qualitatively modeled as distance-based additive forces. Endeavors towards quantita...

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Detalhes bibliográficos

Principais autores:	Koen Minartz, Fleur Hendriks, Simon Martinus Koop, Alessandro Corbetta, Vlado Menkovski
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2025-03-01
coleção:	Scientific Reports
Assuntos:	Crowd dynamics Pedestrian dynamics Active matter physics Generative models Graph neural networks Neural simulators
Acesso em linha:	https://doi.org/10.1038/s41598-025-92566-9
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