Discovering interaction mechanisms in crowds via deep generative surrogate experiments

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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Bibliographic Details
Main Authors: Koen Minartz, Fleur Hendriks, Simon Martinus Koop, Alessandro Corbetta, Vlado Menkovski
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Reports
Subjects:
Crowd dynamics
Pedestrian dynamics
Active matter physics
Generative models
Graph neural networks
Neural simulators
Online Access:https://doi.org/10.1038/s41598-025-92566-9
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https://doi.org/10.1038/s41598-025-92566-9

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