长株潭城际轨道交通客流预测研究

发布时间：2018-05-04 16:00

本文选题：客流预测 + 城际轨道交通　；参考：《长沙理工大学》2012年硕士论文

【摘要】：近年来，我国城市群的快速发展，使得各个城市间的交通需求越来越大。然而，很多中心城市和外围城市间缺乏很好的横向联系，各城市内部的交通结构也存在一定的缺陷。作为一种集大运量、便捷、舒适、准时，“公交化”特点于一体的城际轨道交通运输方式应运而生。客流预测对轨道交通的各个方面和各个阶段都起着及其重要的作用。论文针对长株潭城市群轨道交通进行客流预测研究，首先对城际轨道交通进行基本讨论，详细研究了城际轨道交通的定义、地位和特点，探讨了客流预测的重要性以及主要方法。然后，分析了长株潭城际轨道交通客流时空分布、供需特征及综合交通环境现状。根据现有的行政分区及轨道交通站点设置情况，在划定26个交通小区后，采用四阶段预测法对长株潭城际轨道交通进行客流预测。重点在客流生成阶段，，利用改进后的回归模型和弹性系数法，从两种预测结果选出最合理的结果；客流分布阶段，采用基于土地利用的分布模型来对客流生成量进行分布预测；方式划分阶段，利用旅客意愿调查表中出行者对各种交通方式服务水平的要求和选择交通方式时所持的价值基准，在广义费用计算时重点考虑时间和费用两个影响因素，建立符合本地区实际情况的Logit模型。最后，对客流预测结果进行分时段估算，获得了全日客流量、全日客流周转量、全日分小时段客流量、全日高峰小时客流量等关键定量指标。
[Abstract]:In recent years, with the rapid development of urban agglomeration in China, traffic demand among cities is increasing. However, there is a lack of good horizontal connection between many central cities and peripheral cities, and there are some defects in the internal traffic structure of each city. As a large volume, convenient, comfortable, punctual, "public transport" features in the intercity rail transit mode came into being. Passenger flow prediction plays an important role in all aspects and stages of rail transit. In this paper, the passenger flow prediction of Chang-Zhuzhou-Xiangtan urban agglomeration is studied. Firstly, the basic discussion of intercity rail transit is carried out, and the definition, status and characteristics of intercity rail transit are studied in detail. The importance and main methods of passenger flow prediction are discussed. Then, the spatial and temporal distribution of intercity rail transit passenger flow, the characteristics of supply and demand and the present situation of comprehensive traffic environment are analyzed. According to the existing administrative districts and rail transit stations, the passenger flow of intercity rail transit in Changsha-Zhuzhou-Xiangtan city was forecasted by four-stage forecasting method after 26 traffic districts were delineated. In the stage of passenger flow generation, the most reasonable results are selected from the two forecasting results by using the improved regression model and the elastic coefficient method, and in the passenger flow distribution stage, the distribution model based on land use is used to forecast the passenger flow production. In the mode division stage, using the requirements of travelers' service level of various modes of transportation and the value benchmark held when choosing transportation modes in the passenger willingness questionnaire, two factors, time and cost, are emphatically considered in the generalized cost calculation. The Logit model is established in accordance with the actual situation in this area. Finally, the forecast results of passenger flow are estimated in different periods, and the key quantitative indexes, such as full day passenger flow, full day passenger flow turnover, full hourly passenger flow, full day peak hour passenger flow, are obtained.
【学位授予单位】：长沙理工大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：U293.5;U293.13

【引证文献】