考虑土地利用性质匹配度的城轨客流分布预测  

Forecast of Passenger Flow Distribution among Urban Rail Stations Considering the Land-use Matching Degree

作　　者：姚恩建[1,2] 李斌斌[1,2] 刘莎莎[1,2] 张永生[1,2] 

机构地区：[1]北京交通大学城市交通复杂系统理论与技术教育部重点实验室,北京100044 [2]北京交通大学交通运输学院,北京100044

出　　处：《交通运输系统工程与信息》2015年第6期107-113,共7页Journal of Transportation Systems Engineering and Information Technology

基　　金：科技部'973'(2012CB725403-1);中央高校基本科研业务费专项基金(2014YJS082)

摘　　要：传统城轨站间客流分布模型较少考虑起讫点土地利用对客流分布的影响,当站点周边土地利用发生改变时适用性变差,无法保持较好的预测精度,因此有必要构建考虑站点土地利用及其站点间土地利用性质匹配度的客流分布预测模型.首先,基于站点聚类分析土地利用性质与客流分布之间的关联性,构造性质匹配度指标;其次,综合考虑站点土地利用、性质匹配度、终点站吸引量、运行时间等因素建立效用函数,结合客流数据进行参数估计,构建基于目的地选择的轨道交通客流分布模型;最后,利用广州市轨道交通客流量数据对其进行精度分析.结果显示,在站点土地利用性质未发生改变与改变情景下全网站间客流分布量的平均绝对误差仅为29.30和29.52人,表明模型具有较高的预测精度.Conventional passenger flow distribution forecasting models for urban rail transit rarely consider the impact of station surrounding area＇ s land- use, which results in models＇ accuracies decline dramatically when the land- use around stations changes, so it is necessary to establish the passenger flow distribution forecasting model considering the land-use and their matching degree. First, based on clustering analysis, the matching degree of land-use（MDLU） is defined as an indicator to reflect the correlation between the stations＇ land-use and passenger flow distribution. Second, the urban rail passenger flow distribution forecasting model is established based on the disaggregate theory, in which, the effects of station surrounding area＇ s land- use, MDLU, attraction of destination, travel time and etc. on destination choice behavior are considered. Finally, the passenger flow data collected from Guangzhou metro system is used for the case study, and the result shows that the mean absolute errors of the proposed model are successfully limited to29.30 and 29.52 respectively when the land-use has no-change or change, which demonstrates that the forecasting accuracy of proposed model is satisfactory.

关 键 词：城市交通 客流分布模型 非集计理论 聚类分析 土地利用 

分 类 号：U268.6[机械工程—车辆工程]