Information use by humans during dynamic route choice in virtual crowd evacuations (original) (raw)
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Human responses to multiple sources of directional information in virtual crowd evacuations
The evacuation of crowds from buildings or vehicles is one example that highlights the importance of understanding how individual-level interactions and decision-making combine and lead to the overall behaviour of crowds. In particular, to make evacuations safer, we need to understand how individuals make movement decisions in crowds. Here, we present an evacuation experiment with over 500 participants testing individual behaviour in an interactive virtual environment. Participants had to choose between different exit routes under the influence of three different types of directional information: static information (signs), dynamic information (movement of simulated crowd) and memorized information, as well as the combined effect of these different sources of directional information. In contrast to signs, crowd movement and memorized information did not have a significant effect on human exit route choice in isolation. However, when we combined the latter two treatments with additional directly conflicting sources of directional information, for example signs, they showed a clear effect by reducing the number of participants that followed the opposing directional information. This suggests that the signals participants observe more closely in isolation do not simply overrule alternative sources of directional information. Age and gender did not consistently explain differences in behaviour in our experiments.
Pedestrian and Evacuation Dynamics 2012, 2013
A general challenge during a building emergency evacuation is guiding crowd to the best exits, given potential hazards and blockages due to high density use. Although computer simulation programs such as FDS+Evac allow researchers to evaluate various guidance policies under different circumstances, computational complexity limits their use during an actual emergency. A second limitation of such programs currently available is that they can only model certain psychological variables that affect evacuation. We suggest two innovations to address these difficulties. First, using macroscopic models, mathematical techniques can allow for rapid optimization of guidance that could eventually be used to provide real-time guidance during emergencies. Second, we conduct virtual reality experiments using human participants to provide confirmation of our models, and provide insights into how psychological factors not yet available in FDS+Evac will affect evacuation outcomes. Results of an initial VR experiment are presented.
The Role of Herding Behaviour in Exit Choice during Evacuation
Modelling of human behaviour during emergencies is an important issue to be investigated to improve the safety of transportation infrastructures. This behaviour can be influenced by both the environment (i.e. social influences) and characteristics of the users of infrastructures. The main aim of this paper is to investigate the social influences that push a user to manifest a herding behaviour during evacuations. A behavioural model based on discrete choice models is proposed by using data collected through an on-line survey. This approach is able to highlight the heterogenic tastes of decision makers that may influence this choice in exit behaviour. The results show that decision makers are influenced by both people close to the exit and their socio-economic characteristic.
Modeling human factors influencing herding during evacuation
International Journal of Pervasive Computing and Communications
Purpose It has been witnessed that many incidents of crowd evacuation have resulted in catastrophic results, claiming lives of hundreds of people. Most of these incidents were a result of localized herding that eventually turned into global panic. Many crowd evacuation models have been proposed with different aspects of interests. The purpose of this paper is to attempt to bring together many of these aspects to study evacuation dynamics. Design/methodology/approach The proposed agent-based model, in a hypothetical physical environment, uses perception maps for routing decisions which are constructed from agents’ personal observations of the surroundings as well as information gathered through distant communication. Communication is governed by a trust model which measures the authenticity of the information being shared. Agents are of two types; emotional and rational. The trust model is combined with a game-theoretic model to resolve conflict of agents’ own type with that of types...
A Mixed Logit Model for Predicting Exit Choice during Building Evacuations
Knowledge on human behaviour in emergency is crucial to increase the safety of buildings and transportation systems. Decision making during evacuations implies different choices, of which one of the most important concerns the escape route. The choice of a route may involve local decisions between alternative exits from an enclosed environment. This work investigates the influence of environmental (presence of smoke, emergency lighting and distance of exit) and social factors (interaction with evacuees close to the exits and with those near the decision-maker) on local exit choice. This goal is pursued using an online stated preference survey carried out making use of non-immersive virtual reality. A sample of 1,503 participants is obtained and a Mixed Logit Model is calibrated using these data. The model shows that presence of smoke, emergency lighting, distance of exit, number of evacuees near the exits and the decision-maker, and flow of evacuees through the exits significantly affect local exit choice. Moreover, the model points out that decision making is affected by a high degree of behavioural uncertainty. Our findings support the improvement of evacuation models and the accuracy of their results, which can assist in designing and managing building and transportation systems. The main contribution of this work is to enrich the understanding of how local exit choices are made and how behavioural uncertainty affects these choices.
Investigating Crowd Behaviour during Emergency Evacuations Using Agent-Based Modelling
2005
In the present paper we argue that the effectiveness of interventions/design solutions supporting emergency evacuation of crowds in socio-technical systems, depends on the appropriateness of the models used for the crowd behaviour. After reviewing basic approaches already used to model escaping crowds, the knowledge about crowd behaviour provided by modern social psychology is briefly presented. Agent-based modelling is proposed as an adequate bottom-up approach to model a number of psychological crowd effects on individual psychomotor behaviour, which in turn influence crowd behaviour. The basic features of the agent-based model developed for the passengers of a metro on fire are presented as an example of an escaping crowd, to show the merits of the proposed modelling
Humans do not always act selfishly: social identity and helping in emergency evacuation simulation
To monitor and predict the behaviour of a crowd, it is imperative that the technology used is based on an accurate understanding of crowd psychology. However, most simulations of evacuation scenarios rely on outdated assumptions about the way people behave or only consider the locomotion of pedestrian movement. We present a social model for pedestrian simulation based on self-categorisation processes during an emergency evacuation. We demonstrate the impact of this new model on the behaviour of pedestrians and on evacuation times. In addition to the Optimal Steps Model for locomotion, we add a realistic social model of collective behaviour.
—Applying agent-based modeling to simulate the evacuation in case of emergency situations is recognized by many research works as an efficient tool for understanding the behavior and decision making of occupants in these situations. In this paper, we present our work aiming to modeling the influence of the emotion and social relationship of occupants on their behaviors and decision making in emergency as in case of fire disaster. Firstly, we proposed a formalization of occupants' behavior at group level in emergency situations based on the social theory. This formalization details possible behaviors and actions of people in emergency evacuations, taking into account occupant's social relationship. The formalization will facilitate the construction of simulation for emergency evacuation. Secondly, we modeled the influence of emotion and group behavior on the decision making of occupants in crisis situations. Thirdly, we developed an agent-based simulation that took into account the effect of group and emotion on the decision making of occupants in emergency situations. We conducted a set of experiments allowing to observe and analyze the behavior of people in emergency evacuation.
A model of the decision-making process during pre-evacuation
The behaviour of building occupants before the purposive movement towards an exit, known as the pre-evacuation behaviour, can have a strong impact on the total time required to leave a building in case of fire emergency as well as on the number of casualties and deaths. The preevacuation time can be simulated within computational models using different approaches. This work introduces a new model for the simulation of pre-evacuation behaviour based on the Random Utility Theory. The proposed model represents the pre-evacuation behaviour of simulated occupants considering three behavioural states: normal, investigating and evacuating. The model simulates the probability of choosing to start investigating and evacuating in relation to physical and social environmental factors as well as personal occupant characteristics. These two decisions make occupants pass from their starting normal states to investigating and evacuating states. The paper presents a case study of the proposed pre-evacuation time model using an experimental evacuation data set in a cinema theatre. The application of the model allows identifying the main factors affecting the decision to move from a state to another. In the present case study, the main factors influencing the decisions were the time elapsed since the start of the alarm, the occupant’s position, and social influence. The issues associated with the implementation of the model are discussed.
Journal of Artificial Societies and Social Simulation
Crowd dynamics have important applications in evacuation management systems relevant to organizing safer large scale gatherings. For crowd safety, it is very important to study the evolution of potential crowd behaviours by simulating the crowd evacuation process. Planning crowd control tasks via studying the impact of crowd behavioural evolution towards evacuation simulation could mitigate the possibility of crowd disasters that may happen. During a typical emergency evacuation scenario, conflict among agents occurs when agents intend to move to the same location as a result of the interaction of agents within their nearest neighbours. The effect of the agent response towards their neighbourhood is vital in order to understand the effect of variation of crowd behaviours towards the whole environment. In this work, we model crowd motion subject to exit congestion under uncertainty conditions in a continuous space via computer simulations. We model bestresponse, risk-seeking, risk-averse and risk-neutral behaviours of agents via certain game theory notions. We perform computer simulations with heterogeneous populations in order to study the effect of the evolution of agent behaviours towards egress flow under threat conditions. Our simulation results show the relation between the local crowd pressure and the number of injured agents. We observe that when the proportion of agents in a population of risk-seeking agents is increased, the average crowd pressure, average local density and the number of injured agents get increased. Besides that, based on our simulation results, we can infer that crowd disaster could be prevented if the agent population are full of risk-averse and risk-neutral agents despite circumstances that lead to threat consequences.