Unveiling the Hidden Dimension of Pedestrian Crowds: Introducing Personal Space and Crowding into Simulations.

Models for the automated analysis and simulation of the complex phenomena observable in built environment crowded by pedestrians have been studied for over thirty years. Nonetheless, one of the commonly agreed upon rules guiding regulation of distance among pedestrian, i.e. proxemics, was defined and discussed in static settings, whereas scenarios of interest generally deal with individual and collective movements in crowds. The present paper presents a systemic perspective on the research aimed at defining a dynamic form of proxemics. The paper firstly reports the results of an experiment focused on proxemics and pedestrians personal space, as the hidden dimension of human spatial behavior in crowded environments. We propose a representation of personal space through discrete potentials and an innovative crowding estimation method (i.e. Cumulative Mean Crowding), going beyond simple perceived density evaluation. The experimental setting is introduced and applied to appraise the potential impact of this novel pedestrian perception mechanism on innovative simulation models.