摘要
为研究恐慌心理对紧急情况下人员疏散时间和过程的影响,建立一种基于元胞自动机和改进囚徒困境模型的人员疏散仿真模型;运用该模型考虑恐慌心理对人员疏散路径、速度大小和行为策略的影响;运用此模型分析初始人员密度、环境熟悉度、行为策略比例和行为策略惯性等对恐慌人员疏散规律的影响。研究结果表明:通常情况下,人员疏散时间随着恐慌程度的增加而增加;而在高密度人群聚集且高环境熟悉度情况下,适当提高恐慌程度可降低疏散时间。此外,同一疏散场景下,人员疏散时间的标准差随环境熟悉度的增加而下降。人员在陌生环境陷入高度恐慌时,保持高度的合作行为可显著降低疏散时间;而频繁调整策略则会增加疏散时间。
In order to study the effect of the panic state on the evacuation time and process under an emergency,an evacuation simulation model based on cellular automata and an improved prisoner's dilemma model was established.The model discussed the effect of a panic state on the evacuation path,speed and behavioral strategy.Then,the impacts of initial occupant density,familiarity,behavioral strategy ratio and behavioral strategy inertia on the panicking crowd evacuation were analyzed.The study results show that the evacuation time generally increases as the degree of panic increases.However,an appropriate increase in the degree of panic can reduce the evacuation time under high-density gatherings and a high degree of familiarity with the environment.In addition,the standard deviation of crowd evacuation time for a certain evacuation scenario decreases with the increase of familiarity with the environment.When the occupants in a high degree of panic state are unfamiliar with the environment,maintaining a high degree of cooperative behavior can significantly reduce occupant evacuation time.Frequent adjustment of strategies increases evacuation time when environment familiarity is low.
作者
谢启苗
王焘
王维莉
XIE Qimiao;WANG Tao;WANG Weili(College of Ocean Science and Engineering,Shanghai Maritime University,Shanghai 201306,China;College of Civil Engineering,Hefei University of Technology,Hefei Anhui 230009,China;Institute of Logistic Science and Engineering,Shanghai Maritime University,Shanghai 201306,China)
出处
《中国安全科学学报》
CAS
CSCD
北大核心
2022年第7期180-187,共8页
China Safety Science Journal
基金
国家自然科学基金资助(71503166,71904116)
中国博士后科学基金资助(2021M690851)
上海市“科技创新行动计划”人工智能领域项目(19DZ1209600)。
关键词
恐慌心理
紧急情况
元胞自动机
囚徒困境模型
熟悉度
行为策略
panic state
emergency situation
cellular automata
prisoner's dilemma model
familiarity
behavioral strategy