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针对现今大型活动中的人群踩踏事故频发问题,通过对“鸟巢”演唱会进行人流疏散仿真分析,研究紧急情况下人流疏散逃生规律及均衡疏散方法。通过设置人员速度、移动余值、出口逃生条件等因素扩展元胞自动机行人流模型,并借助Matlab语言实现可视化仿真模拟,以探究人流疏散逃生规律;引入疏散系数,并通过建立BP神经网络获取较优疏散系数,均衡各个出口所承担的疏散任务。结果表明,“鸟巢”演唱会在疏散过程中人群对通行出口的选择较为不合理,仿真疏散总时间长达455.5 s,与理想疏散曲线所得疏散总时间270.0s相比,存在40.7%的偏差,为减小此偏差引入出口疏散系数指导人群定向选择出口,通过仿真模拟得到的疏散总时间为312.0 s,减少约31.5%,出口选择不均衡现象被显著缓解。最后提出了针对疏散不平衡问题的相关措施。
In view of the frequent stampede of people in large-scale activities today, this paper studies the evacuation rules and the method of evacuation evacuation under emergency situations through the evacuation simulation analysis of “Bird’s Nest” concert. The cellular automaton’s pedestrian flow model is extended by setting personnel speed, moving residuals and exit escape conditions, and the simulation simulation is carried out with Matlab language to explore evacuation escape rules; the evacuation coefficient is introduced and BP neural network is used to establish Better evacuation coefficient to balance the evacuation tasks undertaken by each export. The results showed that the crowd selection of entrances and exits in the “Bird’s Nest” concert during the evacuation process was relatively unreasonable. The total time for simulation evacuation was as long as 455.5s, compared with the total evacuation time of ideal evacuation curves of 270.0s, there were 40.7% In order to reduce this discrepancy, the exit evacuation coefficient was introduced to guide the population to choose the outlet. The total evacuation time obtained through simulation was 312.0 s, a decrease of 31.5%. The imbalance of export options was significantly alleviated. Finally, the paper puts forward some measures to solve the problem of unbalanced evacuation.