摘要
文中提出适用的换乘行为分析方法,以提高高铁换乘效率与乘客满意度.论文分析大客流情形下高铁站乘客换乘选择过程与心理,构建基于MNL(Multinomial Logit model)模型、多项式回归模型与NL-RRM(Nested Logit-Random regret-minimization model)模型的三阶段法组合模型,并在NL-RRM模型中引入后悔理论,预测在不同大客流情形下高铁站各换乘方式分担率.结合实际案例探究组合模型的有效性,结果表明:模型t检验值均大于1.96,MNL模型优度比为0.278,NL-RRM模型优度比为0.301,且组合模型命中率明显高于单一MNL模型.
An applicable transfer behavior analysis method was proposed to improve the transfer efficiency and passenger satisfaction of high-speed rail.By analyzing the passenger transfer selection process and psychology in high-speed railway station under the condition of large passenger flow,a three-stage combined model based on MNL(Multinomial Logit model),Polynomial Regression Model and NL-RRM(Nested Logit-Random Regret-Minimization Model)was constructed,and regret theory was introduced into NL-RRM model to predict the sharing rate of various transfer modes in high-speed railway station under different conditions of large passenger flow.Combined with practical cases,the effectiveness of the combined model was explored.The results show that the t-test values of the model are all greater than 1.96,the goodness ratio of MNL model is 0.278,and the goodness ratio of NL-RRM model is 0.301,and the hit rate of the combined model is obviously higher than that of the single MNL model.
作者
江子怡
徐良杰
JIANG Ziyi;XU Liangjie(School of Transportation and Logistics Engineering,Wuhan University of Technology,Wuhan 430063,China;School of Automotive and Traffic Engineering,Hubei University of Arts and Science,Xiangyang 441053,China)
出处
《武汉理工大学学报(交通科学与工程版)》
2025年第1期21-27,共7页
Journal of Wuhan University of Technology(Transportation Science & Engineering)
关键词
高铁站
大客流
换乘行为
后悔理论
NL-RRM模型
high-speed rail stations
large passenger flows
interchange behaviour
regret theory
NL-RRM model
