摘要
综述了一票制公交IC卡乘客下车站点推断的研究现状.为充分利用乘客出行链和站点上车客流量等信息,分析了公交出行的特征,提出了公交出行若干假设条件.在此基础上,定义了相关集合变量来描述单个乘客的出行链,将乘客个体出行特征融入到站点吸引权重的计算中.然后根据乘客出行链信息的完整程度,综合集计分析和非集计分析方法建立了结合出行链的概率模型,并提出了应用模型判断乘客下车站点的算法,以及模型检验方法.最后,以广州公交448路为例,对比了本文模型和单纯非集计分析方法的下车站点判断结果.结果表明,本文提出的模型适用性更广,在集计分析层面具有更高的可靠性.
This paper summarizes the research status of identifying the alighting stations of smart card passengers for flat-rate fare lines.To make best use of passenger trip chains and passenger flow of stations,it analyzes transit travel characteristics and proposes a number of assumptions.Based on these assumptions,it defines relative variables to describe passenger trip chains and considers individual characteristics for alighting attraction weighting.Then,the paper combines disaggregate analysis and aggregate analysis according to the completeness of passenger trip chains and then formulates the bus passenger alighting weight model.It also proposes the algorithm to solve the established model and a calibration method of the model.Finally,it takes Line 448 in Guangzhou city as an example and compared the identifying results of this new model with the identifying results of the disaggregate analysis model.The results show that the new model is more applicative in identifying the alighting stations of smart card passengers and has high reliability in a cluster analysis.
出处
《交通运输系统工程与信息》
EI
CSCD
北大核心
2014年第2期62-67,86,共7页
Journal of Transportation Systems Engineering and Information Technology
基金
国家自然科学基金资助项目(41271181)
2013年广东省安全生产专项资金项目(2013-102)
关键词
智能交通
下车站点
OD估计
出行链
公交IC卡
数据挖掘
intelligent transportation
alighting station
OD estimation
trip chain
smart card
data mining
