Alexander Pfaffinger

Pedestrian Group Behavior in a Cellular Automaton

The study of crowd movement is very important for planning mass events and evacuations. Although many potentially critical incidents are hardly predictable, others like clogging, can be anticipated. Studies have shown that pedestrians in social groups frequently contribute the biggest part to crowds, and that these groups have a significant impact on crowd movement. Furthermore social cooperative behaviour does not stop in emergency situations, but continues or even gets stronger. We employ a cellular automaton with attractive and repulsive potentials for the simulation of individual pedestrians. Then we explain how to integrate a concise model for social groups suitable for the basic modelling techniques. Further aspects of group behavior are discussed, namely large groups and the behavior after a group separation, and we propose a model for these. These investigations lead us to the conclusion that there is a growing need of agent based modelling when facing advanced aspects of pedestrian crowd behavior.

Dynamic Medium Scale Navigation Using Dynamic Floor Fields

This contribution considers a new method for dynamic medium scale navigation in microscopic pedestrian simulators. The concept of static navigation floor fields is extended to a dynamic interpretation following ideas of (Kretz, T, Journal of Statistical Mechanics: Theory and Experiment, P03012, 2009) and (Hartmann, D, New Journal of Physics 12(4):043032, 2010) within a cellular automaton approach. Every few simulation steps a new floor field for navigation is constructed by solving the Eikonal equation on the dual grid of the underlying cellular automaton discretization. By considering other pedestrians directly in the construction of the floor field, the realism of the simulations is significantly increased. The new contribution of our work is to additionally consider walking directions of pedestrians. This leads to a significant increase in the realism of simulations.

Higher Level Programming and Efficient Automatic Parallelization: A Functional Data Flow Approach with FASAN

Adaptive numerical algorithms work recursively on tree-like dynamic data structures rather than iteratively on static arrays. Our approach to parallelize such an algorithm with potentially irregular data structure is a functional program in the coordinating language FASAN. We will show how this concise program can be transformed into a data flow graph which allows both concurrent evaluation and pipelines of sequential functions if combined with the stream semantics of the language. The key issue is the representation of hierarchical data structures as wrapper streams . This concept avoids superfluous communication and synchronization. As an example, we describe the coordinating part of a recursive finite element application.

Waiting Zones for Real Life Scenarios: A Case Study Using a German Railway Station as an Example

Simulations of pedestrian dynamics aim to reproduce and predict the natural behaviour of pedestrians in different situations. In most models it is assumed that pedestrians constantly walk towards their destinations. Here we investigate the legitimacy of this assumption using data, collected during a field experiment and obtained from analysis of video recordings, at a major German railway station. Our observations suggest that a substantial proportion of people stand at certain locations for some time. In order to reproduce the observed behaviour adequately, we enhance an existing cellular automata framework with a new element to model standing persons, the so called waiting zones. Through simulations, we demonstrate how standing persons influence the overall dynamics. We also analyse how the developed model can be used for analysis of critical situations.