(ORDO NEWS) — Day after day, scientists solve the most incredible questions of mankind. For example, how to predict the behavior of a person in a crowd. New theories arrived in time in 2022.
Animal behavior has been helping people get to know themselves better for centuries. This time, scientists have found parallels in the behavior of crowds of people and other animals.
The new model of scientists from Brown University takes into account the point of view of an individual member of the crowd and allows you to predict the possible flow of people in certain circumstances.
The model, described in an article in the journal Proceedings of the Royal Society, illustrates the role of visual perception in the movement of a crowd through each individual, drawing comparisons to flocks of birds or schools of fish.
Such a method departs from previous models that operate from the perspective of an “omniscient observer” (omniscient observer), says study author William H. Warren, professor of cognitive, linguistic and psychological sciences at Brown University.
In other words, in previous studies, the movement of the crowd was analyzed from the point of view of a person observing the crowd from a distance. “Most of the omniscient models were based on physics the forces of attraction and repulsion and didn’t fully explain why people in a group interact the way they do,” Warren said.
Scientists have suggested
“We are the first group to provide a sensory basis for this type of coordinated movement. Our model provides a better understanding of what people in a crowd perceive visually, so we can make more accurate predictions about how an entire group of people will behave,” says Warren.
The new crowd models have many uses and can be used to inform public space design, transportation infrastructure, and emergency response plans.
It is assumed that people in a group use visual information in order to understand which direction to go, speed up or slow down, avoid collisions.
When the researchers used the results of the experiment to create a new theory of collective motion, it successfully predicted individual trajectories in both virtual crowd experiments and real crowd descriptions.
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