摘要
地铁车站运营韧性具有多维性和复杂性。为了准确可靠地评价地铁车站运营韧性水平,提出了1种基于改进CRITIC-VIKOR法的评价方法。基于韧性理论和地铁车站运营特点,明确了地铁车站运营韧性的概念,并阐述了其压力、状态、响应3个维度的内涵。分析地铁车站运营中人、机、环、管这4个方面的关键要素,构建了8个一级指标。通过文献分析,建立了26个二级评价指标。通过采用标准差系数法衡量评价指标,并计算相关系数的绝对值,对CRITIC法进行改进,从而更加合理地给评价指标赋权,并结合VIKOR方法,提出了1种新的地铁车站运营韧性评价模型。对江苏省苏州市地铁4号线的同里站、流虹站、南门站进行实证分析,通过李克特量表收集相关数据,计算得到了26个评价指标的权重和3个车站的群体效用值、个体遗憾值、决策指标值,从而对地铁车站运营韧性进行量化分析和排序。与优序图法、层次分析法、熵值法等赋权方法相比,改进CRITIC法的偏差范围最小,为2%~40%,26个指标累计偏差最小,为553%。研究结果表明:在3个维度韧性中,压力韧性、状态韧性和响应韧性的权重分别为59.74%,21.48%,18.78%。在3个车站中,流虹站的运营韧性最高,其次是同里站和南门站。本文构建的评价模型能够为更加准确地评价地铁车站运营韧性提供理论支持。
The operational resilience of subway stations is characterized by its multidimensionality and complexity.To evaluate this resilience accurately and reliably,an improved A CRITIC-VIKOR based evaluation method is proposed.Based on resilience theory and the operational characteristics of subway stations,the concept of operational resilience for subway stations is defined,with a focus on its three core dimensions:pressure,state,and response.Key factors in four domains,including human,machine,environment,and management,are analyzed,leading to the development of 8 primary indexes.Through literature analysis,26 secondary evaluation indexes are established.To assign more accurate weights to the indexes,the standard deviation coefficient method is applied,improving the CRITIC method through correlation coefficient analysis.By integrating the VIKOR method,a novel evaluation model for subway station operational resilience is proposed.An empirical analysis is conducted on Tongli station,Liuhong station,and Nanmen station of Suzhou subway Line 4.Data is collected using a Likert scale,and weights are calculated for the 26 evaluation indexes,as well as the group utility,individual regret,and decision-making index for each station.This allows for a quantitative ranking of the operational resilience of subway stations.Compared with superiority chart,analytic hierarchy process,and entropy method,the improved CRITIC method showed the smallest bias range,from 2%to 40%,with the cumulative bias of the 26 indexes being the smallest at 553%.The results indicate that the weights for pressure resilience,state resilience,and response resilience are 59.74%,21.48%,and 18.78%,respectively.Among the three stations,Liuhong station demonstrates the highest operational resilience,followed by Tongli station and Nanmen station.The evaluation model provides theoretical foundation for more accurate evaluation of subway station operational resilience.
作者
邓勇亮
高雨桐
周琦
李可为
谷甜甜
DENG Yongliang;GAO Yutong;ZHOU Qi;LI Kewei;GU Tiantian(Suzhou University of Science and Technology,School of Civil Engineering,Suzhou 215009,Jiangsu,China;China University of Mining and Technology,School of Mechanics and Civil Engineering,Xuzhou 221116,Jiangsu,China)
出处
《交通信息与安全》
CSCD
北大核心
2024年第3期167-174,共8页
Journal of Transport Information and Safety
基金
国家自然科学基金项目(71801214)资助。
