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拥挤状态下地铁乘客应激反应的尖点突变分析 被引量:4

Cusp catastrophe based analysis of stress reaction of subway passengers under crowed condition
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摘要 为预防拥挤状态下地铁乘客消极应激反应的发生、提高地铁乘客的积极应激反应能力,用试验法和突变理论,分析地铁乘客应激反应的过程和特点。首先根据地铁设计规范,设计地铁车厢环境;然后测量不同立席密度下,乘客的生理指标;其次将血压(BP)均值和心率(HR)作为尖点突变的控制变量,应激状态作为状态变量,建立地铁乘客应激反应的尖点突变模型;最后对试验数据进行定性拟合和定量拟合分析。结果表明:随着车厢内人群密度的增加,乘客的情绪开始扰动,到达尖点位置时突变,情绪激动;而后乘客慢慢适应人群密度的增加,情绪重新达到稳定;地铁乘客应激反应符合尖点突变模型。 For the sake of preventing the negative stress reaction of subway passengers and improving the active stress response ability,the process and characteristics of subway passengers’stress reaction were studied experimentally and theoretically.A subway car environment was created.Data on heart rate and blood pressure of the passengers were obtained for the density of 1 persons to the density of 10 persons.The mean blood pressure and heart rate were taken as the control variable of point mutation.The stress state was taken as the state variable.A cusp catastrophe model was built for the subway passenger’s stress reaction.Finally,a qualitative fitting analysis and a quantitative fitting analysis were carried out.The results show that the passengers’emotion begins to perturb with the increase of population density,and then changes to the point position,and becomes emotionally excited,and then they will slowly adapt to the increase of population density and return to emotional stability,and that the stress reaction of subway passengers accords with cusp catastrophe model.
作者 林晓飞 宋守信 翟怀远 袁朋伟 陈明利 LIN Xiaofei;SONG Shouxin;ZHAI Huaiyuan;YUAN Pengwei;CHEN Mingli(School of Economics and Management,Beijing Jiaotong University,Beijing 100044,China;Civil Engineering and Agriculture School,Anhui University of technology,Maanshan Anhui 243032,China;Business School,University of Jinan,Jinan Shandong,250022,China)
出处 《中国安全科学学报》 CAS CSCD 北大核心 2019年第2期112-117,共6页 China Safety Science Journal
基金 国家自然科学基金资助(B16A300010) 国家社会科学基金资助(13AZD088 17CGL073)
关键词 地铁乘客 拥挤 应激反应 测量试验 尖点突变 数据拟合 subway passengers crowding stress reaction measurement and experiment cusp catastrophe data fitting
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