Abstract 

There has been a significant increase in the modelling, analysis and calibration of models for pedestrian crowds in the last years. In this talk I will present different mathematical models for crowds - such as the social force model as well as a minimal macroscopic model for unidirectional flows - and discuss their respective analytical and computational challenges. I will then focus on the problem of estimating parameters in macroscopic pedestrian models using trajectory data. I will use the Bayesian framework to perform the identification and analyse the performance of the developed methodologies for different experimental settings.