This title appears in the Scientific Report :
2019
Please use the identifier:
http://dx.doi.org/10.1016/j.ijdrr.2019.101295 in citations.
Characteristics of pedestrian's evacuation in a room under invisible conditions
Characteristics of pedestrian's evacuation in a room under invisible conditions
In this paper, movement characteristics of pedestrian's evacuation under invisible conditions are investigated through a series of evacuation experiments. The typical evacuation behaviors of occupants including moving along walls as well as different conflict resolutions are observed. Moreover,...
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Personal Name(s): | Cao, Shuchao (Corresponding author) |
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Liu, Xiaodong / Chraibi, Mohcine / Zhang, Peng / Song, Weiguo | |
Contributing Institute: |
Zivile Sicherheitsforschung; IAS-7 |
Published in: | International journal of disaster risk reduction, 41 (2019) S. 101295 - |
Imprint: |
Amsterdam [u.a.]
Elsevier
2019
|
DOI: |
10.1016/j.ijdrr.2019.101295 |
Document Type: |
Journal Article |
Research Program: |
Computational Science and Mathematical Methods |
Publikationsportal JuSER |
In this paper, movement characteristics of pedestrian's evacuation under invisible conditions are investigated through a series of evacuation experiments. The typical evacuation behaviors of occupants including moving along walls as well as different conflict resolutions are observed. Moreover, individual evacuation time, movement distance, distance to walls and individual velocity during evacuations are analyzed based on the extracted trajectories. Spatial distribution of evacuees is quantified by using the variance-mean ratio and the nearest-neighbor analysis. It is found that evacuees are randomly distributed in the room at the beginning of evacuation. However, after the start of the experiment, individuals search cautiously their surrounding and start to walk along walls. Under this circumstance aggregated distributions are formed. This study is helpful to understand pedestrian's behavior and develop efficient guidance strategy for crowds under poor visibility. Moreover, the data obtained from the experiment can be used for model validation under invisible conditions. |