Speed modulated social influence in evacuating pedestrian crowds

Evacuation is a complex social phenomenon with individuals tending to exit a confined space as soon as possible. Social factors that influence an individual include collision avoidance and conformity with others with respect to the tendency to exit. While collision avoidance has been heavily focused on by the agent-based models used frequently to simulate evacuation scenarios, these models typically assume that all agents have an equal desire to exit the scene in a given situation. It is more likely that, out of those who are exiting, some are patient while others seek to exit as soon as possible. Here, we experimentally investigate the effect of different proportions of patient (no-rush) versus impatient (rush) individuals in an evacuating crowd of up to 24 people. Our results show that a) average speed changes significantly for individuals who otherwise tended to rush (or not rush) with both type of individuals speeding up in the presence of the other; and b) deviation rate, defined as the amount of turning, changes significantly for the rush individuals in the presence of no-rush individuals. We then seek to replicate this effect with Helbing's social force model with the twin purposes of analyzing how well the model fits experimental data, and explaining the differences in speed in terms of model parameters. We find that we must change the interaction parameters for both rush and no-rush agents depending on the condition that we are modeling in order to fit the model to the experimental data

New approaches to evacuation modelling for fire safety engineering applications

This paper presents the findings of the workshop “New approaches to evacuation modelling”, which took place on the 11th of June 2017 in Lund (Sweden) within the Symposium of the International Association for Fire Safety Science (IAFSS). The workshop gathered international experts in the field of fire evacuation modelling from 19 different countries and was designed to build a dialogue between the fire evacuation modelling world and experts in areas outside of fire safety engineering. The contribution to fire evacuation modelling of five topics within research disciplines outside fire safety engineering (FSE) have been discussed during the workshop, namely 1) Psychology/Human Factors, 2) Sociology, 3) Applied Mathematics, 4) Transportation, 5) Dynamic Simulation and Biomechanics. The benefits of exchanging information between these two groups are highlighted here in light of the topic areas discussed and the feedback received by the evacuation modelling community during the workshop. This included the feasibility of development/application of modelling methods based on fields other than FSE as well as a discussion on their implementation strengths and limitations. Each subject area is here briefly presented and its links to fire evacuation modelling are discussed. The feedback received during the workshop is discussed through a set of insights which might be useful for the future developments of evacuation models for fire safety engineering

Application of Virtual Reality in the study of Human Behavior in Fire : Pursuing realistic behavior in evacuation experiments

Virtual Reality (VR) experiments are used to study human behavior in fire because they allow simulation of fire events with relatively low risks to the participants, while maintaining high levels of experimental control. Manystudies have used VR experiments to explore aspects of the human response to fire threats, but VR experiments as a research method are yet to be subjected to a systematic process of validation. One way to validate VR experiments is to compare VR data to data obtained using other research methods, e.g., case studies, laboratory experiments, and field experiments. Five independent VR experiments were designed to collect data that could be then compared to data collected using other research methods. Both datasets, VR and physical, are thencompared with each other to assess similarities and differences between them. Results show that participants in the VR experiments often acted like people did in the physical-world events. Moreover, Human Behavior in Fire theories that explain the behavior of victims in real fires were found to also explain the participants’ behavior in the VR experiments. There were differences between VR and physical-world samples, which highlighted limitations of VR experiments or aspects about realism that need to be considered when designing VR experiments. Visual realism is not enough for participants to interpret a virtual fire emergency as a threat. Therefore, VR experiments need to induce participants to take the virtual fire event seriously. Social norms that apply in physical world contexts may not emerge naturally in virtual environments, and measures should be taken to enhance behavioral realism in VR. These findings are a meaningful contribution to the development of the VR experiment method for collection of behavioral data

Human factors investigation of the behavioural response to cues of a fire emergency

Safety is a significant priority in the contemporary building environment and a focus for many organisations and businesses. Studies have been conducted to review different factors regarding human behaviour during fire evacuation and to utilize the findings to model improved egress procedures and to train occupants on how to evacuate safely. However, much is still unknown about the processes of perceiving and responding to an emergency when cues from different information sources conflict. For example, when a fire evacuation warning has been issued, but the conditions in the area appear to be fine, some of the building occupants may have uncertainty about the correct action to take. There are several cues to an emergency, and some of these may not lead to optimum behaviour. For example, prior research has shown that, in cases where there has been a prevalence of nuisance alarms such as false alarms, occupants may not take action when a real fire alarm is sounded (Proulx, 2007). Moreover, cues to an emergency are often ambiguous and may not be immediately perceived as a threat. This research was conducted to understand the human responses to cues of an emergency in greater detail. It was based on the Protective Action Decision Model (PADM) (Lindell & Perry, 2012), which outlines the research framework conducted within this PhD. PADM provides a formal model of human behaviour during an emergency. Still, it should be expanded into a more comprehensive method of predicting how people behave in a fire or an evacuation (Kuligowski, 2013). The PADM model identifies several stages in the process of emergency detection and response. The first stage defines several factors that influence awareness of a fire scenario; environmental and social contexts, information sources, warning messages, channel access, and receiver characteristics. This PhD conducted a series of experimental studies to identify the influence of some of these factors on user response to fire alarm cues. The research also compared the use of different research methods, specifically, scenario talk through and virtual reality (VR) simulation, to evaluate user behaviour in response to a fire alarm. Four studies have been conducted: the first extended the talk-through method previously used by Lawson et al. (2013) by adding the influence of social cues to the fire scenario. The second study presented the same fire scenario and influence of social cues as study 1, using VR. The pattern of results was consistent with previous literature in that passive behaviour of others resulted in longer evacuation times for the participants. Thus, these methods can reveal the influence of social behaviour on predicting human responses to an emergency. Study three extended the VR scenario to include other factors from stage one of the PADM model. These factors include the source of information during an emergency, the content of the information, and the recipient's characteristics. Therefore, the source of information, level of details, and information channels were all identified as significant in emergencies such as fire evacuations. Finally, the fourth study was conducted to understand the effects of social cues (passive or active conflict) on an authority figure or siren in the evacuation process. Again, three groups were identified and exposed to three different messages in a virtual environment. Results showed that an authority figure in an active conflict situation showed a significant reduction in the evacuation times. Thus, this thesis will show that understanding behavioural response to fire emergency cues has potential value in predicting human behaviour in a fire emergency

Human factors investigation of the behavioural response to cues of a fire emergency

Safety is a significant priority in the contemporary building environment and a focus for many organisations and businesses. Studies have been conducted to review different factors regarding human behaviour during fire evacuation and to utilize the findings to model improved egress procedures and to train occupants on how to evacuate safely. However, much is still unknown about the processes of perceiving and responding to an emergency when cues from different information sources conflict. For example, when a fire evacuation warning has been issued, but the conditions in the area appear to be fine, some of the building occupants may have uncertainty about the correct action to take. There are several cues to an emergency, and some of these may not lead to optimum behaviour. For example, prior research has shown that, in cases where there has been a prevalence of nuisance alarms such as false alarms, occupants may not take action when a real fire alarm is sounded (Proulx, 2007). Moreover, cues to an emergency are often ambiguous and may not be immediately perceived as a threat. This research was conducted to understand the human responses to cues of an emergency in greater detail. It was based on the Protective Action Decision Model (PADM) (Lindell & Perry, 2012), which outlines the research framework conducted within this PhD. PADM provides a formal model of human behaviour during an emergency. Still, it should be expanded into a more comprehensive method of predicting how people behave in a fire or an evacuation (Kuligowski, 2013). The PADM model identifies several stages in the process of emergency detection and response. The first stage defines several factors that influence awareness of a fire scenario; environmental and social contexts, information sources, warning messages, channel access, and receiver characteristics. This PhD conducted a series of experimental studies to identify the influence of some of these factors on user response to fire alarm cues. The research also compared the use of different research methods, specifically, scenario talk through and virtual reality (VR) simulation, to evaluate user behaviour in response to a fire alarm. Four studies have been conducted: the first extended the talk-through method previously used by Lawson et al. (2013) by adding the influence of social cues to the fire scenario. The second study presented the same fire scenario and influence of social cues as study 1, using VR. The pattern of results was consistent with previous literature in that passive behaviour of others resulted in longer evacuation times for the participants. Thus, these methods can reveal the influence of social behaviour on predicting human responses to an emergency. Study three extended the VR scenario to include other factors from stage one of the PADM model. These factors include the source of information during an emergency, the content of the information, and the recipient's characteristics. Therefore, the source of information, level of details, and information channels were all identified as significant in emergencies such as fire evacuations. Finally, the fourth study was conducted to understand the effects of social cues (passive or active conflict) on an authority figure or siren in the evacuation process. Again, three groups were identified and exposed to three different messages in a virtual environment. Results showed that an authority figure in an active conflict situation showed a significant reduction in the evacuation times. Thus, this thesis will show that understanding behavioural response to fire emergency cues has potential value in predicting human behaviour in a fire emergency

Social influence on evacuation behavior in real and virtual environments

Virtual reality (VR) is a promising tool to study evacuation behavior as it allows experimentally controlled, safe simulation of otherwise dangerous situations. However, validation studies comparing evacuation behavior in real and virtual environments are still scarce. We compare the decision to evacuate in response to a fire alarm in matched physical and virtual environments. 150 participants were tested individually in a one-trial experiment in one of three conditions. In the Control condition, the fire alarm sounded while the participant performed a bogus perceptual matching task. In the Passive bystander condition, the participant performed the task together with a confederate who ignored the fire alarm. In the Active bystander condition, the confederate left the room when the fire alarm went off. Half of the participants in each condition experienced the scenario in the real laboratory, and the other half in a matched virtual environment with a virtual bystander, presented in a head-mounted display. The active bystander group was more likely to evacuate, and the passive bystander group less likely to evacuate, than the control group. This pattern of social influence was observed in both the real and virtual environments, although the overall response to the virtual alarm was reduced; positive influence was comparable, whereas negative influence was weaker in VR. We found no reliable gender effects for the participant or the bystander. These findings extend the bystander effect to the decision to evacuate, revealing a positive as well as the previous negative social influence. The results support the ecological validity of VR as a research tool to study evacuation behavior in emergency situations, with the caveat that effect sizes may be smaller in VR