首页|Immersive virtual reality experiments for emergency evacuation response in deep underground space

Immersive virtual reality experiments for emergency evacuation response in deep underground space

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Safe evacuation of crowds from deep underground spaces is challenging owing to large building sizes, enclosed indoor spaces, and long upward-evacuation distances. A virtual-reality (VR) scenario was created to study human behavior during fire emergencies in deep underground space, and a series of immersive VR experiments for evacuation was conducted. The experiment investigated evacuee pre-movement time (also called pre-evacuation time or response delay) and its distribution characteristics in deep underground space, in addition to their exit-selection ratio under five factors: left-right habituation, crowd effect, visibility, spatial familiarity, and luminance. A post-experiment questionnaire also examined participant impressions of aspects such as the realism and emotion of the VR experience. The results show that pre-movement time was shorter in deep underground space than in aboveground buildings and shallow underground space. Individual pre-movement time was significantly influenced both by their real experience with fire emergencies and whether the student participants majored in architecture. Spatial familiarity, crowd effect, and visibility had a more significant impact on human decision-making overall. Left-right habituation and luminance are less influential; crowd effect reinforces under-risk behavior and a sense of grouping, when crowd effect and visibility reduction work together. The study conclusions are likely to influence future VR-evacuation experiments and fire-safety design. The empirical data can also be input into computer simulations that model building evacuations. Quantifying experimental data on pedestrian behavior is essential for developing performance-based evacuation safety designs in deep underground spaces.

Immersive virtual realityDeep underground spaceHuman behavior in firePre-movement timeExit selectionEXIT CHOICEBEHAVIORDESIGNSTANDARDSMOVEMENTDYNAMICSMODELTIMES

Wang, Chong、Li, Chao、Zhou, Tiejun、Wang, Dachuan、An, Xiaoxiao、Lv, Jiayue、Wang, Jie

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Chongqing Univ

Chongqing Univ||Chongqing University School of Civil Engineering||Chongqing Univ

Southwest Univ Sci & Technol

China Railway Siyuan Survey & Design Inst Grp Co L

Chongqing Planning & Design Inst

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2025

Tunnelling and underground space technology

Tunnelling and underground space technology

SCI
ISSN:0886-7798
年,卷(期):2025.163(Sep.)
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