Do people follow the crowd in building emergency evacuation? A cross-cultural immersive virtual reality-based study

Lin, Jing; Zhu, Runhe; Li, Nan; Becerik-Gerber, Burçin

doi:10.1016/j.aei.2020.101040

Cited by 118 publications

(41 citation statements)

References 50 publications

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“…Previous searchers put forward many psychological theories to describe evacuees' herb behavior as "the need to behave in the same way as everyone else does" [40,41], which is also found in economics and business fields. Similar phenomena occur during the evacuation, evacuees prefer the crowded door as the exit.…”

Section: Discussionmentioning

confidence: 99%

“…(2) Stimulation of the partially-favorable strategy FS i k (t) of door k The herding effect [31,40] is highlighted in the existing literature regarding seismic evacuation, which stresses that an agent often tries to keep the same moving direction and speed of the crowd. However, in a homogeneous environment, anomalies are always more likely to be observed and imitated [41,42]. As shown in Figure 1b, a small group was stimulated and quickly separated from the "sheep".…”

Section: Conditionmentioning

confidence: 94%

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Dynamic Decision-Making Process of Evacuees during Post-Earthquake Evacuation near an Automatic Flap Barrier Gate System: A Broken Windows Perspective

Song

Liu

2021

Sustainability

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The automatic flap barrier gate system (AFBGS) plays a critical role in building security, but it is more vulnerable to natural hazards than common exits (including power failure, due to earthquakes, and delayed evacuation, due to safety certification, etc.). This article considers a dynamic decision-making process of evacuees during post-earthquake evacuation near an AFBGS. An interesting metaphor, broken windows (BW), is utilized to interpret people’s actual behavior during evacuation. A multi-stage decision-making mechanism of evacuees is developed to characterize the instantaneous transition among three defined stages: Habitual, mild, and radical states. Then, we build a modified three-layer social force model to reproduce the interaction between evacuees based on an actual post-earthquake evacuation. The simulations reveal that BW provides a contextualized understanding of emergency evacuation with a similar effect to the traditional metaphor. An earlier appearance of a mild rule breaker leads to a higher crowd evacuation efficiency. If evacuees maintain the state of broken windows behavior (BWB), the crowd evacuation efficiency can be improved significantly. Contrary to the criminological interpretation, the overall effect of mild BWB is positive, but the radical BWB is encouraged under the command of guiders.

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Section: Discussionmentioning

confidence: 99%

Section: Conditionmentioning

confidence: 94%

Dynamic Decision-Making Process of Evacuees during Post-Earthquake Evacuation near an Automatic Flap Barrier Gate System: A Broken Windows Perspective

Song

Liu

2021

Sustainability

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“…In the real emergency escape, the moving speed of people is generally 0.1–1.98 m/s [ 50 ]. In the virtual reality scenes, Lin et al [ 51 ] set the moving speed of the virtual character as a fixed value of 2.4 m/s, and Cosma et al [ 52 ] set this speed as 1.2 m/s. In order to avoid motion sickness caused by moving too fast or slow, here we set a constant speed of 1.5 m/s through several trials, with an Xbox joystick in hand to move or make turns in the virtual subway fire escape.…”

Section: Methodsmentioning

confidence: 99%

Experimental Study on the Evaluation and Influencing Factors on Individual’s Emergency Escape Capability in Subway Fire

Chen

Zhao

Gao

et al. 2021

IJERPH

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Studying an individual’s emergency escape capability and its influencing factors is of great practical significance for evacuation and escape in subway emergencies. Taking Zhengzhou Zijing Mountain Subway station as the prototype, and using VR technology, a virtual subway fire escape scene was built. Combined with the total escape time, the total contact time with fire, and the total contact time with smoke, it proposed a calculation formula on emergency escape capability. A total of 34 participants with equal gender distribution were recruited to carry out the virtual subway fire escape experiment, and participants’ physiological data (heart rate variability, skin conductance) were real-time recorded by ErgoLAB V3.0 throughout the whole experiment. The emergency escape capability of each participant was evaluated quantitatively, and the related influencing factors were analyzed. The results show that for the age ranges (19–22 years old) in the experiment, the emergency escape capability of women is significantly lower than that of men (p < 0.05); although there is no significance in emergency escape capability in DISC personality types (p > 0.05), the mean emergency escape capability of people with influence personality type is the worst, and that of people with compliance type is the best; during virtual fire escape vs. baseline, Mean_SC and Mean_HR both increased very significantly (all p < 0.01), and participants were under stress during their virtual fire escape. There is a significant negative correlation between emergency escape capability and LF_increase_rate (p < 0.05), and a remarkably significant negative correlation between emergency escape capability and LF/HF_increase_rate (p < 0.01); the greater the increase rate of LF or LF/HF, the smaller the emergency escape capability, with excessive stress probably not being conducive to emergency escape. There is a very significant negative correlation between an individual’s emergency escape capability and the degree of familiarity with the Zijing Mountain subway station (p < 0.01). The findings provide references and suggestions on the emergency management and emergency evacuation for government and subway departments.

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“…In addition to training, VR can also be used for monitoring the specific behavior and cognitive state of individuals. A cross-cultural VR-based investigation of evacuation patterns of crowds in fire emergencies was successfully able to study the influence of the cognitive state of stress on evacuation behavior of individuals [ 11 ]. These studies demonstrate the promise of VR to effectively prepare medical professionals for emergencies such as natural disasters, mass casualties, etc.…”

Section: Introductionmentioning

confidence: 99%

Brain Activity-Based Metrics for Assessing Learning States in VR under Stress among Firefighters: An Explorative Machine Learning Approach in Neuroergonomics

et al. 2021

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The nature of firefighters` duties requires them to work for long periods under unfavorable conditions. To perform their jobs effectively, they are required to endure long hours of extensive, stressful training. Creating such training environments is very expensive and it is difficult to guarantee trainees’ safety. In this study, firefighters are trained in a virtual environment that includes virtual perturbations such as fires, alarms, and smoke. The objective of this paper is to use machine learning methods to discern encoding and retrieval states in firefighters during a visuospatial episodic memory task and explore which regions of the brain provide suitable signals to solve this classification problem. Our results show that the Random Forest algorithm could be used to distinguish between information encoding and retrieval using features extracted from fNIRS data. Our algorithm achieved an F-1 score of 0.844 and an accuracy of 79.10% if the training and testing data are obtained at similar environmental conditions. However, the algorithm’s performance dropped to an F-1 score of 0.723 and accuracy of 60.61% when evaluated on data collected under different environmental conditions than the training data. We also found that if the training and evaluation data were recorded under the same environmental conditions, the RPM, LDLPFC, RDLPFC were the most relevant brain regions under non-stressful, stressful, and a mix of stressful and non-stressful conditions, respectively.

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Do people follow the crowd in building emergency evacuation? A cross-cultural immersive virtual reality-based study

Cited by 118 publications

References 50 publications

Dynamic Decision-Making Process of Evacuees during Post-Earthquake Evacuation near an Automatic Flap Barrier Gate System: A Broken Windows Perspective

Dynamic Decision-Making Process of Evacuees during Post-Earthquake Evacuation near an Automatic Flap Barrier Gate System: A Broken Windows Perspective

Experimental Study on the Evaluation and Influencing Factors on Individual’s Emergency Escape Capability in Subway Fire

Brain Activity-Based Metrics for Assessing Learning States in VR under Stress among Firefighters: An Explorative Machine Learning Approach in Neuroergonomics

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