The investigation of pedestrian dynamics is a young and lively field of research. Along with interesting self-organization phenomena there is a multitude of applications, like the evaluation of escape routes in the context of crowd management or the optimization of pedestrian facilities for urban development. Our aim is the quantitative description of pedestrian dynamics by using microscopic models of self-driven particle systems. For model validation the group cooperates with several universities on a systematic enhancement of the empirical data basis.
The group has taken a pioneering role in the conception and execution of large-scale laboratory experiments involving pedestrians. This covers the automatic extraction of information (for instance trajectories) from experiments video footages using pattern recognition techniques and the analysis and evaluation of the information using high standard methods based on Voronoi decompositions. The field is completed by the development of high accurate models for pedestrian dynamics which are used in simulations to reproduce the observed phenomena. Furthermore, to increase the transparency of the research activities and promote a sustainable development, the models and analysis tools developed so far are available to the scientific community in the form of open source projects combined with databases of experimental results.
PeTrack - Automatic Extraction of Pedestrian Trajectories from Video Recordings
JuPedSim - Framework for performing pedestrian simulations
Routing - Route Choice in Pedestrian Dynamics
Modeling the shape of pedestrians in 2d space
Analysis and measurement of experiments
Database - collection of own experimental data