Crowd_Evacuation_Wargaming_dataset
收藏DataCite Commons2025-04-04 更新2025-04-16 收录
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资源简介:
This dataset constitutes the outcomes of simulations conducted in accordance with the model outlined in the paper titled "Wargame Thinking Reshaping Evacuation Dynamics: A Crowd Evacuation Model with Real-Time Emotional Adaptation." It encompasses four sub-datasets: Group_1_Experiment_Evacuation_Efficiency, Group_2_Experiment_Stampede_Characteristics_Analysis, Group_3_Experiment_Thermal_Impact_Assessment, and Group_4_Experiment_Emotion_Coefficient_Influence. This dataset can be employed to explore evacuation efficiency, investigate stampede characteristics during evacuation procedures, analyze the influence of environmental temperature on the evacuation process, and examine the role of emotions in evacuation scenarios. Data analysis reveals the occurrence of arching phenomena during evacuation, with individuals closer to fallen pedestrians being more prone to panic. Additionally, environmental temperature reduction was found to correlate with a notable increase in fall incidents, while the emotional decay rate demonstrated significant negative correlations with evacuation duration. These findings provide practical insights for refining crowd management strategies and emotional intervention protocols during evacuation procedures.
本数据集基于《博弈思维重塑疏散动力学:一种具备实时情绪自适应的人群疏散模型》一文中提出的模型开展模拟实验所得的结果。该数据集包含四个子数据集:Group_1_Experiment_Evacuation_Efficiency(组1疏散效率实验)、Group_2_Experiment_Stampede_Characteristics_Analysis(组2踩踏特征分析实验)、Group_3_Experiment_Thermal_Impact_Assessment(组3热影响评估实验)以及Group_4_Experiment_Emotion_Coefficient_Influence(组4情绪系数影响实验)。本数据集可用于探究疏散效率、分析疏散过程中的踩踏特征、评估环境温度对疏散流程的影响,以及研究情绪在疏散场景中的作用。数据分析表明,疏散过程中会出现拱状阻塞现象(arching phenomena),离摔倒行人更近的个体更易陷入恐慌。此外,研究发现环境温度降低与摔倒事件的显著增加呈正相关,而情绪衰减速率与疏散时长则呈现显著负相关关系。上述研究结果可为优化疏散过程中的人群管理策略与情绪干预规程提供实践参考。
提供机构:
Mendeley Data创建时间:
2025-04-04
搜集汇总
背景与挑战
背景概述
该数据集基于一篇关于实时情绪适应的人群疏散模型的论文,通过模拟生成了四个子数据集,用于研究疏散效率、踩踏特征、环境温度影响和情绪作用。分析揭示了疏散过程中的拱形现象、恐慌传播模式、温度降低导致跌倒事件增加,以及情绪衰减率与疏散时间呈负相关,为优化人群管理和情绪干预策略提供了实践依据。
以上内容由遇见数据集搜集并总结生成



