基于混合模型的综合客运枢纽离站客流疏导效果评价研究

Research on evaluation of passenger departure effect in comprehensive passenger transport hub based on hybrid model

针对枢纽离站客流疏导效果评价定量化研究不足的问题,提出了一种离站客流疏导效果量化分析评价方法。根据客运枢纽内部交通接驳方式,对客运枢纽进行功能区划分;对客流离站过程细化分析,建立综合枢纽客流疏导效果评价指标体系;根据评价指标体系二级指标特征,基于聚类算法对历史客流数据进行疏导效果等级划分;基于综合AHP和熵权法双重优势的双层混合模型对客流疏导效果进行评价。以重庆北站北广场为例进行分析,研究结果表明:重庆北站工作日疏导效果评价等级指数在2.0~3.0,疏导效果一般;非工作日评价等级指数在2.0~4.0,疏导效果一般;节假日评价等级指数在2.0~5.0,疏导效果较差。大客流情况下,轨道交通功能区客流疏导评价等级指数平均增长14%,其余功能区平均增长之和为7%,说明大客流情况下,轨道交通对客流疏导作用较强。

The de-station passenger flow diversion capacity of a comprehensive passenger transport hub directly affects the operation efficiency and service level of the entire hub. Aiming at the problem of insufficient quantitative research on the evaluation of the de-station passenger flow diversion effect of the hub, a quantitative analysis and evaluation method for the de-station passenger flow diversion effect is proposed. According to the internal traffic connection mode of the passenger transportation hub, the passenger transportation hub is divided into functional areas;the detailed analysis of the passenger departure process is applied to establish a comprehensive hub passenger flow diversion effect evaluation index system;according to the secondary index characteristics of the evaluation index system, the clustering algorithm is used to analyze historical passenger flow data which is used to classify the diversion effect;the two-layer hybrid model based on the dual advantages of comprehensive AHP and entropy weight method is used to evaluate the diversion effect of passenger flow. Taking the North Square of Chongqing North Railway Station as an example, the research results show that the evaluation grade index of Chongqing North Railway Station’s work day dredging effect is between 2.0 and 3.0, and the effect is average;the non-working day evaluation grade index is between 2.0 and 4.0, and the dredging effect is average. The effect is average;the holiday evaluation grade index is between 2.0 and 5.0, and the dredging effect is poor. In the case of large passenger flow, the traffic in the rail function area of the passenger flow guidance evaluation index increased by an average of 14%, and the average increase in the other functional areas is 7%.