Disaster behaviorUnderstanding crowd behavior in disasters
Researchers have developed a new model for the behavior of pedestrians and crowds; most simulation software is often based on physics-inspired assumptions, such as repulsive forces between pedestrians; the new, psychologically based model, in contrast, assumes that pedestrians try to minimize the coverage of their vision field, while adjusting the walking speed to keep a safety distance from other people; the new approach can help in understanding and preventing tragic crowd disasters, developing better architectural designs and new navigation approaches in robotics
Crowd movement shows defineable patterns // Source: unc.edu
During rush hours, every train station is flooded with people on the way to or from work. The crowds stream from the tracks to the exits, the escalators, the bus stops. Despite this, collisions are rare. Sometimes one person makes way, sometimes another, but everyone gets to the destination amazingly quickly. Mehdi Moussaid and Guy Theraulaz from the Centre national de la recherche scientifique (CNRS) in Toulouse and Dirk Helbing from Eidgenössische Technische Hochschule Zürich (ETH Zurich) have now developed a simple cognitive model that explains how pedestrians move and how the surprising self-organization of human flows comes about.
Computer simulation models of pedestrian and crowd behavior are not new. Today’s simulation software, however, is often based on physics-inspired assumptions, such as repulsive forces between pedestrians. The new, psychologically based model, in contrast, assumes that pedestrians try to minimize the coverage of their vision field, while adjusting the walking speed to keep a safety distance from other people. It is based on two heuristic rules — decisions that people make without much thinking about their behavior. If you combine these rules with the contact forces that occur in extremely high pedestrian densities, the model can also realistically depict crowd disasters.
Hunting for gaps
Previously it was assumed that each obstacle has a repulsive effect on pedestrians. The new approach instead assumes that pedestrians are seeking gaps, and that groups are perceived as a whole. In contrast to previous models, which decompose a pedestrian’s environment into separate effects, the new approach describes the scene in a holistic, integrated manner. In response to a complex environment, a person may re-align, slow down his or her steps or deviate from a certain direction to avoid collisions. Nevertheless, nobody realistically calculates thousands of variations to select the optimum route. That is done, for example, by some approaches in robotics, where people are sometimes seen as a homo economicus, that is, strict optimizers. It is, however, sufficient to apply simple rules to find the almost perfect path of minimum effort through the crowd, says Helbing.
Approach simpler than expected
The researchers verified their model with different data sets, from the single individual up to flows of pedestrians at bottlenecks and in evacuation situations. Never before were so many different tests conducted to support a model, says Helbing, but this was necessary since the new model represents a paradigm shift. It is a scientific breakthrough, because experts believed that a cognitive
