Cumulative Mean Crowding and Pedestrian Crowds: A Cellular Automata Model

摘要

Cellular Automata simulations of crowd dynamics can support the design of transportation facilities in terms of efficiency, comfort and safety. The development of realistic CA models requires the acquisition of empirical evidences about human individual and collective behavior. The paper reports the results of controlled experiments of personal space in static and dynamic situations: the area surrounding human body, linked to crowding due to spatial intrusion/restriction. We propose a discrete representation of personal space through discrete potentials and an innovative crowding estimation method (i.e. Cumulative Mean Crowding). Simulation results are focused on the parametric evaluation of pedestrians' psychological stress reaction to density.