Adaptive pedestrian behaviour for the preservation of group cohesion

A crowd of pedestrians is a complex system in which individuals exhibit conflicting behavioural mechanisms leading to self-organisation phenomena. Computer models for the simulation of crowds represent a consolidated type of application, employed on a day-to-day basis to support designers and decision makers. Most state of the art models, however, generally do not consider the explicit representation of pedestrians aggregations (groups) and their implications on the overall system dynamics. This work is aimed at discussing a research effort systematically exploring the potential implication of the presence of groups of pedestrians in different situations (e.g. changing density, spatial configurations of the environment). The paper describes an agent-based model encompassing both traditional individual motivations (i.e. tendency to stay away from other pedestrians while moving towards the goal) and an adaptive mechanism representing the influence of group presence in the simulated population. The mechanism is designed to preserve the cohesion of specific types of groups (e.g. families and friends) even in high density and turbulent situations. The model is tested in simplified scenarios to evaluate the implications of modelling choices and the presence of groups. The model produces results in tune with available evidences from the literature, both from the perspective of pedestrian flows and space utilisation, in scenarios not comprising groups; when groups are present, the model is able to preserve their cohesion even in challenging situations (i.e. high density, presence of a counterflow), and it produces interesting results in high density situations that call for further observations and experiments to gather empirical data. The introduced adaptive model for group cohesion is effective in qualitatively reproducing group related phenomena and it stimulates further research efforts aimed at gathering empirical evidences, on one hand, and modelling efforts aimed at reproducing additional related phenomena (e.g. leader-follower movement patterns)

Towards an Application of Graph Structure Analysis to a MAS-based model of Proxemic Distances in Pedestrian Systems

Abstract—This paper proposes the use of methods for network analysis in order to study the properties of a dynamic graph that model the interaction among agents in an agent-based model. This model is based on Multi Agent System definition and simulates a multicultural crowd in which proxemics theory and distance perception are taking into account. After a discussion about complex network analysis and crowd research context, an agent-based model based on SCA*PED (Situated Cellular Agents for PEdestrian Dynamics) approach is presented, based on two separated yet interconnected layers representing different aspects of the overall system dynamics. Then, an analysis of network derived from agent interactions in the Proxemic layer is proposed, identifying characteristic structures and their meaning in the crowd analysis. At the end an analysis related to the identification of those characteristic structures in some real examples is proposed. I

Dealing with crowd crystals in MAS-based crowd simulation: A proposal

The paper presents an agent-based model for the explicit representation of groups of pedestrians in a crowd. The model is the result of a multidisciplinary research (CRYSTALS project) where multicultural dynamics and spatial and socio-cultural relationships among individuals are considered as first class elements for the simulation of crowd of pilgrims taking to the annual pilgrimage towards Makkah. After an introduction of advantages of Multi-Agent System approach for pedestrian dynamics modelling, a formal description of the model is proposed. The scenario in which the model was developed and some examples about modelling heterogeneous groups of pedestrians are described