Stress estimation in pedestrian crowds: Experimental data and simulations results

Issue title: Emotional Machines: The Next Revolution

Guest editors: Valentina Franzoni, Alfredo Milani, Daniele Nardi and Jordi Vallverdú

Article type: Research Article

Authors: Gorrini, Andrea^{a; *} | Crociani, Luca^a | Vizzari, Giuseppe^a | Bandini, Stefania^{a; b}

Affiliations: [a] Complex Systems and Artificial Intelligence research center, Department of Informatics, Systems and Communication, University of Milano-Bicocca, Italy. E-mails: [email protected], [email protected], [email protected], [email protected] | [b] Research Center for Advanced Science and Technology, The University of Tokyo, Japan

Correspondence: [*] Corresponding author. E-mail: [email protected].

Abstract: Agent-based simulations of pedestrian crowd dynamics can support the design of transportation facilities in terms of efficiency, comfort and safety. The development of realistic models requires the acquisition of empirical evidences about human behavior. The paper reports the results of an experiment of pedestrian personal space: 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), introducing also the notion of shared personal space among group members. Simulation results are focused on the parametric estimation of pedestrians’ psychological stress reaction to density.

Keywords: Pedestrian crowds, crowding, personal space, grouping, modeling and simulations

DOI: 10.3233/WEB-190403

Journal: Web Intelligence, vol. 17, no. 1, pp. 85-99, 2019