Researchers at Brown University developed a new model to predict human flocking behavior based on optics and other sensory data.
March 21, 2022
Artificial Intelligence
Visual Processing
Basic Research
Grantee
Data Science and Health Informatics
Like flocks of birds or schools of fish, crowds of humans also tend to move en masse — almost as if they’re thinking as one. Scientists have proposed different theories to explain this type of collective pedestrian behavior.
A new model from researchers at Brown University takes the point of view of an individual crowd member, and is remarkably accurate at predicting actual crowd flow, its developers say.
The model, described in a Proceedings of the Royal Society B paper, illustrates the role of visual perception in crowd movement. It shows how crowd members who are visible from a participant’s viewpoint determine how that participant follows the crowd and what path they take.