The movements of a crowd are not chaotic but predictable.
Crowds intimidate and even terrify some people. Their movements can lead to tragedy. That is why it is essential to understand them better. A new study shows that these movements are not chaotic, as one might imagine, but rather almost circular and periodic.
François Gu, Massachusetts Institute of Technology (MIT) and Benjamin Guiselin, University of Montpellier
You've probably experienced being in a dense crowd in a confined space: on crowded subway platforms during rush hour, in front of a store for the release of a best-selling author's latest book, or in front of the stage at a concert. Beyond the discomfort caused by frequent, involuntary physical contact with those around you, these situations seem uncontrollable and potentially dangerous: you feel compelled to move according to a rhythm dictated by impatience or pressure from others. But what is the true nature of individuals' movements within a dense crowd? And can we understand their origin, particularly in order to anticipate tragedies?
If we trust our intuition, these movements seem random and unpredictable. However, our study, conducted within the team of Denis Bartolo, professor at ENS Lyon, and recently published in the journal Nature, reveals a counterintuitive phenomenon: instead of disorderly chaos, the crowd moves collectively in a regular and spontaneous manner. Beyond a critical density of four people per square meter (imagine four people in a shower stall!), and without any external instructions, the crowd spontaneously adopts a quasi-circular and periodic movement.
Our experience: the festivities in Pamplona and its "Chupinazo"
Our first challenge in characterizing the dynamics of dense crowds was a daunting one: conducting experiments to film the dynamics of hundreds of individuals from a good angle, while avoiding accidents. It was therefore obvious that we couldn't do this in our laboratory. The ideal opportunity arose when Iker Zuriguel, a professor at the University of Navarra, told us about the San Fermín festival in Spain. Every year on July 6, around 5,000 people gather at Plaza Consistorial in Pamplona for the "Chupinazo" ceremony, which marks the start of a week of festivities. The density reaches around 6 people per square meter!
This square, which measures 50 meters long by 20 meters wide, is surrounded by multi-story buildings, whose balconies offer a breathtaking view of what is happening in the square. We filmed four editions with eight cameras placed on two balconies, capturing the movements of the crowd in very high resolution. We have thus collected a dataset that is unique in the world for the study of dense crowds.
The crowd sways in unison
Using a technique employed in aerodynamics, for example, we were able to map the speeds of movement within the crowd, much like tracking air currents around an airplane. We concluded that all individuals within a radius of approximately 10 meters were moving in the same direction.
During the Chupinazo, the crowd density is very high, around six people per square meter: imagine around 500 people being pulled together spontaneously, representing a mass of several dozen tons in motion.
We also showed that the direction of movement of this mass gradually rotated before returning to its starting point every 18 seconds. In other words, individuals do not move chaotically, but follow quasi-circular and periodic trajectories.
This slow movement can be explained by the fact that it is not isolated individuals who are moving, but several hundred people, moving together.
Finally, we observed that the oscillating circular movements of the crowd occur both clockwise and counterclockwise, even though the majority of human beings are right-handed ortend to avoid each other on the right in Western countries. Cognitive and biological factors are therefore no longer relevant in explaining the movement of large numbers of individuals in dense crowds that are caught up in large-scale movements.
The origin of spontaneous crowd oscillation
To mathematically model the dynamics of a crowd consisting of a group of pedestrians, it seems natural to consider individuals as interacting particles.
Take a pedestrian in this crowd. They are subject to forces that set them in motion. These forces may be physical in origin—such as contact with a wall or another pedestrian—or cognitive in origin—such as when trying to avoid another pedestrian. Unfortunately, mathematical modeling of these forces relies on numerous unverifiable assumptions about individual behavior, making this approach unworkable.
In reality, it is not necessary to describe the dynamics of each individual to predict the dynamics of the crowd. Take the flow of water in a pipe: the laws of physics make it possible to predict the flow of water, even though it is impossible to determine the force exerted on a single water molecule in this flow.
We therefore determined the equation that would describe the movement of a mass of individuals moving together, without determining the laws governing the movement of a single pedestrian. Our approach uses only fundamental principles of physics (conservation of mass, conservation of momentum) and makes no behavioral assumptions about the movement of individuals. It enabled us to construct a mathematical model whose solution showed excellent agreement with experimental observations.
A new method for preventing crowd accidents?
We also analyzed videos from surveillance cameras at the 2010 Love Parade in Duisburg, Germany. Although this crowd was very different from the one at the Chupinazo, we observed the same collective oscillations. This suggests that this mass behavior is universal, regardless of the type of event or the profile of the participants.
As we pointed out earlier, these oscillations can set several dozen tons in motion. We believe that such an uncontrolled movement of mass can become dangerous. During the Chupinazo, no accidents have ever been reported, probably because the event is short (one to two hours) and participants come of their own free will, with a certain awareness of the risks. This was not the case during the 2010 Love Parade, where an accident caused dozens of deaths and hundreds of injuries. Just before the accident occurred, we detected these oscillations.
This detection can be done in real time, based on a direct and simple analysis of CCTV cameras. And since this dynamic is universal, the same method could be applied to other crowds. Thus, our findings could, in the future, inspire the development of tools for detecting and preventing mass accidents.
François Gu, Postdoctoral Fellow, Massachusetts Institute of Technology (MIT) and Benjamin Guiselin, Associate Professor of Physics, University of Montpellier
This article is republished from The Conversation under a Creative Commons license. Readthe original article.