Fakultät für Maschinenbau und Sicherheitstechnik

Pedestrian and evacuation dynamics

    
The topics are about modeling pedestrian movement in two dimensions using physics-based models (differential systems) and pedestrian trajectory prediction in crowded situations by deep learning approaches (artificial neural networks). The focuses are on self-organization and collective behaviors, experiment-based modeling, evacuation dynamics, or large-scale simulation.

In fine, the objectives are to develop simulation tools for building architecture, urban infrastructure, or large events and mass gatherings evaluation under different regulation strategies.

    
Focuses

  Collision-free pedestrian model

  Pedestrian trajectory prediction by supervised machine-learning

  Large-scale simulation

  Tactical model for the exit choice

  Modelling mixed urban traffic

    
NetLogo pedestrian simulation modules

  First order collision-free model

  Social force model

  Simulation of lane and band formation

Reviews on pedestrian dynamics

M. Boltes, J. Zhang, A. Tordeux, A. Schadschneider and A. Seyfried, Empirical results of pedestrian and evacuation dynamics, Encyclopedia of Complexity and Systems Science, vol. 16, pp. 1-29, 2018. Springer Berlin, Germany.

M. Chraibi, A. Tordeux, A. Schadschneider and A. Seyfried, Modelling of pedestrian and evacuation dynamics, Encyclopedia of Complexity and Systems Science, pp. 1-22, 2018. Springer Heidelberg.

A. Schadschneider, M. Chraibi, A. Seyfried, A. Tordeux and J. Zhang, Pedestrian dynamics: From empirical results to modeling, in Crowd Dynamics, Volume 1, Springer, 2018, pp. 63-102.

    

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