Dynamical models for pedestrian dynamics using data from pedestrian flow sensors

The purpose of this thesis is to give a contribution in a wider project regarding the development of new tools for the governance of tourist flows in Venice. Because of the virus COVID-19, this topic has increased in interest, since it can be used both to look for possible solutions to make public places safer and to study the spread of the virus itself. Once the testing of the sensors that provide the data on mobility is carried out, a macroscopic approach to the pedestrian dynamics based on the Fundamental Diagram is proposed: scenarios with different geometries as streets, crossroads or bridges are compared, focusing in particular on representative parameters of the model. In the last part, a microscopic approach to pedestrian mobility is presented: a simulation model is calibrated on the basis of the available data, in order to define whether it can actually reproduce the behaviour of a crowd.