铁道科学与工程学报2026，Vol.23Issue(8)：4032-4045,14.DOI:10.19713/j.cnki.43-1423/u.T20251564
基于多源信息分析的铁路隧道模拟火灾环境下人员疏散行为研究
Study on passenger evacuation behavior in high-altitude railway tunnel fire environments based on multi-source data analysis
摘要
Abstract
With the rapid expansion of high-speed railway networks,the number and length of tunnels in mountainous regions have increased,and poor ventilation has raised fire risks while elevating physiological load and emotional stress among passengers.To clarify the physiological,psychological,and behavioral responses of passengers during fire evacuations,identify key evacuation stages,and propose targeted optimization strategies,a simulated fire evacuation experiment was conducted in a real-scale railway tunnel.Multi-source data,including evacuation behavior,subjective psychological states,and physiological signals,were synchronously collected and analyzed.Non-parametric statistical tests(Mann-Whitney U test)were employed to compare multi-source responses under different evacuation strategies and stages.The results show that(1)evacuation strategy and prior experience significantly influenced passengers'physiological and psychological responses.Compared with unilateral evacuation,bilateral evacuation improved evacuation efficiency by 0.39 s per person,reduced the mean panic score from 4.16 to 3.78,and decreased physiological variation levels.(2)Physiological indicators related to alertness were significantly correlated with evacuation speed;and individuals with higher alertness evacuated 1.15 m/s faster per person,indicating that moderate alertness can enhance evacuation efficiency.(3)The door area acted as a bottleneck,eliciting pronounced physiological activation and negative emotions such as panic and anxiety.Statistical results confirmed significant differences in physiological indicators before and after passing the door area(p<0.001).Subjective evaluations indicated that crew guidance effectively alleviated negative emotions,with an average effectiveness score of 4.25/5.These findings provide quantitative evidence and theoretical support for optimizing evacuation strategies and management in railway tunnel fire scenarios.关键词
铁路隧道/火灾事故/人员生理-心理-行为/多源信息分析/疏散策略Key words
railway tunnel/fire incident/personnel physiology-psychology-behavior/multi-source data analysis/evacuation strategy分类
交通工程引用本文复制引用
韩得民,谢宝超,林书翔,陈沛桢,周丹,范超杰,彭勇,梁习锋..基于多源信息分析的铁路隧道模拟火灾环境下人员疏散行为研究[J].铁道科学与工程学报,2026,23(8):4032-4045,14.基金项目
国家自然科学基金资助项目(U24B20123) （U24B20123）
中南大学校企联合合作项目(2023XQLH019) （2023XQLH019）
