Computer Science Department, ETH Zurich
In this talk, I am going to look back to how the field of pedestrian, crowd and evacuation dynamics emerged in physics, and how it developed over time. I will give a very personal perspective, with many anecdotes and background stories. Modeling pedestrians and crowds as self-driven many-particle systems has turned out to be a surprisingly powerful approach to model and understand the dynamics of humans moving through space while interacting with others. Besides driven particle and cellular automata models, the Social Force Model is certainly one of the models that was inspired by physics and was able to reproduce several interesting collective patterns of motion, which emerge by self-organization. These patterns include the formation of lanes of uniform walking direction in bidirectional flows, stripe formation in two crossing flows, and oscillatory flows at bottlenecks. Such discoveries, including the faster is slower effect, have inspired improvements in logistics (chip production) and in traffic light control, and it does not stop there. Modern experimental techniques, for example, use Virtual Reality technology combined with multi-agent simulations, to reconstruct crowd disasters as they have happened in the past.