Simulating crowd evacuation with socio-cultural, cognitive, and emotional elements

In this research, the effects of culture, cognitions, and emotions on crisis management and prevention are analysed. An agent-based crowd evacuation simulation model was created, named IMPACT, to study the evacuation process from a transport hub. To extend previous research, various socio-cultural, cognitive, and emotional factors were modelled, including: language, gender, familiarity with the environment, emotional contagion, prosocial behaviour, falls, group decision making, and compliance. The IMPACT model was validated against data from an evacuation drill using the existing EXODUS evacuation model. Results show that on all measures, the IMPACT model is within or close to the prescribed boundaries, thereby establishing its validity. Structured simulations with the validated model revealed important findings, including: the effect of doors as bottlenecks, social contagion speeding up evacuation time, falling behaviour not affecting evacuation time significantly, and travelling in groups being more beneficial for evacuation time than travelling alone. This research has important practical applications for crowd management professionals, including transport hub operators, first responders, and risk assessors

An Information Perception-Based Emotion Contagion Model for Fire Evacuation

In fires, people are easier to lose their mind. Panic will lead to irrational behavior and irreparable tragedy. It has great practical significance to make contingency plans for crowd evacuation in fires. However, existing studies about crowd simulation always paid much attention on the crowd density, but little attention on emotional contagion that may cause a panic. Based on settings about information space and information sharing, this paper proposes an emotional contagion model for crowd in panic situations. With the proposed model, a behavior mechanism is constructed for agents in the crowd and a prototype of system is developed for crowd simulation. Experiments are carried out to verify the proposed model. The results showed that the spread of panic not only related to the crowd density and the individual comfort level, but also related to people’s prior knowledge of fire evacuation. The model provides a new way for safety education and evacuation management. It is possible to avoid and reduce unsafe factors in the crowd with the lowest cost

Simulating Evacuation Crowd with Emo-tion and Personality

Crowd evacuation has attracted great attention, the number of emergencies continues to increase. Thanks to the technology, it is possible to deduce the behavior of the crowd in emergencies, improving security. The multitude enters into a state of panic, so it is necessary to have action protocols for these situations. This work tries to establish a multi-agent model of emotional contagion that simulates the behavior of the crowd in an evacuation. The method is proposed for closed areas such as supermarkets, stadiums, soccer, stadiums, etc. The emotional contagion will accelerate the evacuation, but the congestion will occur if the panic emotion is spread too fast

Agent-based models of social behaviour and communication in evacuations:A systematic review

Most modern agent-based evacuation models involve interactions between evacuees. However, the assumed reasons for interactions and portrayal of them may be overly simple. Research from social psychology suggests that people interact and communicate with one another when evacuating and evacuee response is impacted by the way information is communicated. Thus, we conducted a systematic review of agent-based evacuation models to identify 1) how social interactions and communication approaches between agents are simulated, and 2) what key variables related to evacuation are addressed in these models. We searched Web of Science and ScienceDirect to identify articles that simulated information exchange between agents during evacuations, and social behaviour during evacuations. From the final 70 included articles, we categorised eight types of social interaction that increased in social complexity from collision avoidance to social influence based on strength of social connections with other agents. In the 17 models which simulated communication, we categorised four ways that agents communicate information: spatially through information trails or radii around agents, via social networks and via external communication. Finally, the variables either manipulated or measured in the models were categorised into the following groups: environmental condition, personal attributes of the agents, procedure, and source of information. We discuss promising directions for agent-based evacuation models to capture the effects of communication and group dynamics on evacuee behaviour. Moreover, we demonstrate how communication and group dynamics may impact the variables commonly used in agent-based evacuation models

Agent-based models of social behaviour and communication in evacuations: A systematic review

Most modern agent-based evacuation models involve interactions between evacuees. However, the assumed reasons for interactions and portrayal of them may be overly simple. Research from social psychology suggests that people interact and communicate with one another when evacuating and evacuee response is impacted by the way information is communicated. Thus, we conducted a systematic review of agent-based evacuation models to identify 1) how social interactions and communication approaches between agents are simulated, and 2) what key variables related to evacuation are addressed in these models. We searched Web of Science and ScienceDirect to identify articles that simulated information exchange between agents during evacuations, and social behaviour during evacuations. From the final 70 included articles, we categorised eight types of social interaction that increased in social complexity from collision avoidance to social influence based on strength of social connections with other agents. In the 17 models which simulated communication, we categorised four ways that agents communicate information: spatially through information trails or radii around agents, via social networks and via external communication. Finally, the variables either manipulated or measured in the models were categorised into the following groups: environmental condition, personal attributes of the agents, procedure, and source of information. We discuss promising directions for agent-based evacuation models to capture the effects of communication and group dynamics on evacuee behaviour. Moreover, we demonstrate how communication and group dynamics may impact the variables commonly used in agent-based evacuation models.Comment: Pre-print submitted to Safety Science special issue following the 2023 Pedestrian and Evacuation Dynamics conferenc

Behavioral Human Crowds and Society

This chapter provides an introduction to the contents of this edited volume. In keeping with the style of the previous edited volumes, we also consider research perspectives. The first part of this chapter contributes to the selection of some key perspectives that take into account not only the technical interest of modeling and simulation, but also the impact that this research activity can have on the well-being of society. The second part provides a brief introduction to the contents of the chapters that follow this editorial introduction. The contents of the chapter refer both to the aforementioned key topics and to the contents of the preceding edited volumes (Bellomo and Gibelli, Behavioural human crowds, recent results towards new research frontiers. In: Bellomo, Gibelli (eds) Crowd dynamics, Volume 3 - Modeling and social applications in the time of COVID 19. Birkhäuser, New York, pp 1–9, 2021; Bellomo et al., Behavioural human crowds. In: Gibelli (ed) Crowd dynamics, Volume 2 - Theory, models, and applications. Birkhäuser, New York, pp 1–10, 2020; Gibelli and Bellomo, Behavioral human crowds. In: Crowd dynamics, Volume 1 - Theory, models, and safety problems. Birkhäuser, New York, pp 1–14, 2018).</p