Theinvestigationofcrowddynamicsisacomplexfieldofstudy that involves different types of knowledge and skills, and, also from the socio-psychological perspective, the definition of crowd is still controver- sial. We propose to investigate analytically this phenomenon focusing on pedestrian dynamics in medium-high density situations, and, in particu- lar, on proxemic behavior of walking groups. In this work we will present several results collected during the observation of the incoming pedes- trian flows to an admission test at the University of Milano-Bicocca. In particular, we collected empirical data about: levels of density and of service, group spatial arrangement (degree of alignment and cohesion), group size and composition (gender), walking speed and lane formation. The statistical analysis of video footages of the event showed that a large majority of the incoming flow was composed of groups and that groups size significantly affects walking speed. Collected data will be used for an investigative modeling work aimed at simulating the observed crowd and pedestrian dynamics.

Federici, M., Gorrini, A., Manenti, L., Vizzari, G. (2012). Data Collection for Modeling and Simulation: Case Study at the University of Milan-Bicocca. In Cellular Automata (pp. 699-708). Springer [10.1007/978-3-642-33350-7_72].

Data Collection for Modeling and Simulation: Case Study at the University of Milan-Bicocca

Federici, M;GORRINI, ANDREA;MANENTI, LORENZA ALESSANDRA;VIZZARI, GIUSEPPE
2012

Abstract

Theinvestigationofcrowddynamicsisacomplexfieldofstudy that involves different types of knowledge and skills, and, also from the socio-psychological perspective, the definition of crowd is still controver- sial. We propose to investigate analytically this phenomenon focusing on pedestrian dynamics in medium-high density situations, and, in particu- lar, on proxemic behavior of walking groups. In this work we will present several results collected during the observation of the incoming pedes- trian flows to an admission test at the University of Milano-Bicocca. In particular, we collected empirical data about: levels of density and of service, group spatial arrangement (degree of alignment and cohesion), group size and composition (gender), walking speed and lane formation. The statistical analysis of video footages of the event showed that a large majority of the incoming flow was composed of groups and that groups size significantly affects walking speed. Collected data will be used for an investigative modeling work aimed at simulating the observed crowd and pedestrian dynamics.
Capitolo o saggio
Crowd, Pedestrian Dynamics, Groups, Proxemics
English
Cellular Automata
2012
978-3-642-33349-1
7495
699
708
Federici, M., Gorrini, A., Manenti, L., Vizzari, G. (2012). Data Collection for Modeling and Simulation: Case Study at the University of Milan-Bicocca. In Cellular Automata (pp. 699-708). Springer [10.1007/978-3-642-33350-7_72].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/37305
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