PUBLIC LECTURE: Mathematics and Statistics Colloquium

We propose a model-free approach to analyse the movement of pedestrians in experiments and simulations. Using concepts from control and analysis of complex dynamical systems we set up a scheme which allows us to identify dynamical unstable signatures in pedestrian flows. These signatures are the building blocks for crowd control and soft management of people. Our approach is entirely data driven and we provide a proof of concept by field and laboratory experiments. In addition, our approach provides, based on experimental observations, quantitative benchmarks to judge the quality of mathematical models for pedestrian motion.