An improved social force model (ISFM)-based crowd evacuation simulation method in virtual reality with a subway fire as a case study

Autor: Jinbin Zhang, Jun Zhu, Pei Dang, Jianlin Wu, Yuxuan Zhou, Weilian Li, Lin Fu, Yukun Guo, Jigang You
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: International Journal of Digital Earth, Vol 16, Iss 1, Pp 1186-1204 (2023)
Druh dokumentu: article
ISSN: 1753-8947
1753-8955
17538947
DOI: 10.1080/17538947.2023.2197261
Popis: Crowd evacuation simulation using virtual reality (VR) is significant for digital emergency response construction. However, existing evacuation simulation studies suffer from poor adaptation to complex environments, inefficient evacuations, and poor simulation effects and do not fully consider the impacts of specific disaster environments on crowd evacuation. To more realistically express the crowd evacuation results obtained under the influence of fire environments and the subjective consciousness of pedestrians in subway stations, we designed a dynamic pedestrian evacuation path planning method under multiple constraints, analysed the influences of an ‘environmental role’ and a ‘subjective initiative’ on crowd evacuation, established an improved social force model (ISFM)-based crowd evacuation simulation method in VR, developed a prototype system and conducted experimental analyses. The experimental results show that the crowd evacuation time of the ISFM is affected by the disaster severity. In simulation experiments without disaster scenarios, the improved model's crowd evacuation efficiency improved by averages of 12.53% and 15.37% over the commercial Pathfinder software and the original social force model, respectively. The method described herein can effectively support real-time VR crowd evacuation simulation under multiexit and multifloor conditions and can provide technical support for emergency evacuation learning and management decision analyses involving subway fires.
Databáze: Directory of Open Access Journals
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