Control of collective human behavior: Social dynamics beyond modeling

Abstract

The motion of pedestrians is a paradigmatic phenomenon to study collective human behavior. We propose a model-free approach to analyze the movement of pedestrians in experiments and get a quantitative understanding of crowd dynamics. Using concepts from control and analysis of 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 and thus result in a fundamental understanding of collective human behavior. Our approach is entirely data driven, and we provide a proof of concept using field and laboratory experiments. In addition, this methodology provides, based on experimental observations, quantitative benchmarks to judge the quality of mathematical models for pedestrian motion.