A landscape of crowd-management support: An integrative approach

Abstract

Of the many crowd behavior models, very few have been used in assisting crowd management practice. This lack of usage is partly due to crowd management involving a diversity of situations that require competencies in observing, sense-making, anticipating and acting. Crowd research is similarly scattered across disciplines and needs integration to advance the field towards supporting practice. To address these needs, we present INCROWD, an integrated framework detailing a high-level architecture of a decisionsupport system for crowd management and model development. It also offers a lens for categorizing crowd literature, allowing us to present a structured literature review.

On the interplay between behavioral dynamics and social interactions in human crowds

“…The various models proposed in the last decades were derived referring to a general mathematical structure, suitable to capture the complexity features of large systems of interacting entities, and hence suitable to provide the conceptual basis towards basis for the derivation of specific models, which are derived by implementing the said structure by heuristic models of individual based interactions. On the other hand, recent papers by researchers involved in the practical management of real crowd dynamics problems, including crisis and safety problems, have enlighten that social phenomena pervade heterogeneous crowds and can have an important influence on the interaction rules [7,16,23,24,25,31,32,37,41,43,44]. Therefore, both social and mechanical dynamics, as well as their complex interactions, should be taken into account.…”

“…The growing interest for this research field is motivated by the potential benefits for the society. As an example, the realistic modeling of human crowds can lead to simulation tools to support crisis managers to handle emergency situations, as sudden and rapid evacuation through complex venues, where stress induced by overcrowding, or even social conflicts may affect safety of the people [20,27,29,37,41].…”

Simulation Research on Safe Flow Rate of Bidirectional Crowds Using Bayesian‐Nash Equilibrium

“…As macroscopic models study overall pedestrian flows and ignore the heterogeneity and complexity of individuals, they are unable to accurately analyze the mechanisms between the microscopic pedestrian behavior and the macroscopic phenomena of the crowd. Therefore, microscopic models have been the main methods used for pedestrian flow research [12][13][14][15]. Table 1 summarizes recent research on pedestrian flows.…”

Prediction and Diversion Mechanisms for Crowd Management Based on Risk Rating

“…For example, crowd behavior models grounded in science originate from different disciplines including psychology, sociology, theoretical physics, applied mathematics, artificial intelligence and computer science have been established to help stakeholders better understand crowd behavior, but only few have been actually used to assist in crowd management, maybe partly because crowd behaviors are of significant uncertainties while some models either coming in different forms or ranging from extremely formal or implicit knowledge are not ready for use [5]. Simultaneously, technological tools and proposals about crowd organization and venue design have been offered for particular aspects of crowd management, but most of them are not for usability in practice.…”