Predicting how large numbers of visitors to major events will behave is difficult, even using evidence based on past experience. To prevent disasters, police, rescue services, and event organizers have to be able to identify dangerous bottlenecks, hidden obstacles, and unexpected escape routes in advance.
A research group at Technische Universität München (TUM) in Germany has developed a simulator that can be used to compute different scenarios at specific venues. The program can simulate the behavior of tens of thousands of people, making emergency management significantly easier.
The simulator has been developed by researchers from a number of universities and companies in collaboration with the authorities and security services in Kaiserslautern. The scientists had access to the topography of the area around the Fritz-Walter soccer stadium as well as data on the fans, and research findings on the behavior of large crowds. To better understand how pedestrians get from A to B in an unfamiliar city, the researchers sent 150 first-semester students from the main TUM building to Munich’s Hofbräuhaus. The students took a wide variety of routes, but provided useful patterns. The majority, for example, chose long, straight routes and used prominent locations as a guide.
The simulator is programmed on the basis of a force model in which destinations, obstacles, and other people all exert a force on individual pedestrians. One of the challenges was to model these forces in such a way that the program can be applied to all possible scenarios and behavior patterns because different people act in different ways. While some already know the routes they need to take, others first have to find their bearings.
The program is designed as a training simulator that users can operate themselves. The microscopic simulation represents every individual in a crowd of 10,000, thus enabling security and emergency services to meticulously track the consequences of specific decisions in real-life situations. Color-coded crowd densities and real-time simulations make it a particularly user friendly application, especially as conventional microscopic simulations usually require a long time to compute.
In the future, it should be possible to program a simulator like this for any major event where – as in the case of Kaiserslautern – visitors have specific destinations, and programmers have knowledge of topography of the area in question as well as the general size and composition of the crowd. The model cannot be applied to locations such as amusement parks, where visitors walk around without any specific destination. Similarly, it cannot be used to simulate panic situations, where people no longer act rationally.