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

Issue title: Interdisciplinary Nature of Information Processing Special Issue Dedicated to Giancarlo Mauri on the Occasion of His 70th Birthday

Guest editors: Alberto Dennunzio, Gheorghe Păun, Grzegorz Rozenberg and Claudio Zandron

Article type: Research Article

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

Affiliations: [a] CSAI research center, Department of Informatics, Systems and Communication, University of Milano-Bicocca, Viale Sarca 336, 20126, Milano, Italy | [b] RCAST, The University of Tokyo, Komaba Campus, 4-6-1 Meguro-ku, 153-8904, Tokyo, Japan | [c] CSAI research center, Department of Informatics, Systems and Communication, University of Milano-Bicocca, Viale Sarca 336, 20126, Milano, Italy. giuseppe.vizzari@unimib.it

Correspondence: [†] Address for correspondence: CSAI research center, Department of Informatics, Systems and Communication, University of Milano-Bicocca, Viale Sarca 336, 20126, Milano, Italy

Note: [*] Also afiliated as: RCAST, The University of Tokyo, Meguro-ku, 153-8904, Tokyo, Japan

Abstract: 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.

Keywords: Modeling and Simulations, Cellular Automata, Pedestrian Crowds, Crowding

DOI: 10.3233/FI-2020-1870

Journal: Fundamenta Informaticae, vol. 171, no. 1-4, pp. 19-38, 2020