[1]陈君,吕玉坤,崔美莉.基于出行模式的公交IC卡乘客下车站点判断方法[J].西安建筑科技大学学报(自然科学版),2018,50(01):23-29.[doi:10.15986/j.1006-7930.2018.01.005]
　CHEN JunL Yukun,CUI Meili.Estimating alighting stops of smart card public transportation passengers based on travel patterns[J].J. Xi’an Univ. of Arch. & Tech.(Natural Science Edition),2018,50(01):23-29.[doi:10.15986/j.1006-7930.2018.01.005]
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基于出行模式的公交IC卡乘客下车站点判断方法()
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西安建筑科技大学学报（自然科学版）[ISSN:1006-7930/CN:61-1295/TU]

卷:
50
期数:
2018年01期
页码:
23-29
栏目:
出版日期:
2018-03-15

文章信息/Info

Title:
Estimating alighting stops of smart card public transportation passengers based on travel patterns
文章编号:
1006-7930(2018)01-0023-07
作者:
陈君1; 吕玉坤1; 2; 崔美莉1
(1.西安建筑科技大学 土木工程学院,陕西 西安 710055 ;2.中铁四局集团设计研究院,安徽 合肥 230023 )
Author(s):
CHEN Jun1L Yukun1; 2;  CUI Meili1
(1. School of Civil Engineering, Univ. of Arch. & Tech., Xian, 710055, China 2. Design and Research Institute of CTCE Group, Hefei 230023, China)
关键词:
公共交通; 出行模式; 出行链; 下车站点; IC卡数据
Keywords:
public transportation;  travel patterns;  trip chain;  alighting stop;  smart card data
分类号:
U491.1
DOI:
10.15986/j.1006-7930.2018.01.005
文献标志码:
A
摘要:
对智能公交系统数据进行分析和挖掘,能够为城市公共交通系统的规划和管理提供科学的决策依据.一票制的公交IC卡收费系统仅在上车时刷卡，乘客下车站点的信息无法直接得到，而现有方法只能判断出部分乘车记录的下车站点,这成为公交IC卡数据应用的制约因素.根据公交乘客出行的时空规律性，提出基于通勤出行模式和关联出行模式判断下车站点的思路.利用通勤出行规律判断公交乘客的通勤OD，再根据其居住地和工作地站点信息对通勤出行的下车站点进行估计.依据公交乘客长期出行具有一定时空关联性的规律，通过将当日出行与他日的关联出行数据进行匹配来判断下车站点.对提出的方法进行算法实现，并应用大规模实际数据对算法进行了实验和精度分析.研究结果表明：该方法能够有效提高下车站点的判断比例，准确率达到87.90%，能够应用于实际的公交系统规划和管理工作
Abstract:
Analyzing and mining the data of Advance Public Transportation Systems can provide scientific decision-making basis for urban public transportation planning and management. In flat-rate automated fare collection system, alighting stops information of the passengers is not available directly. The existing method can only determine part of alighting stops, which is a limiting factor for the application of smart card data. According to time-spatial regularity of transit travel, this paper presents the method of estimating alighting stops based on commuting travel patterns and related travel patterns. Commuting OD is judged by commuting regularity, and then the alighting stops of commuting trips are estimated on the basis of commuters′ residences and work places. Based on long-term time-spatial correlation of travels, alighting stops are estimated by matching the related travels. The algorithm was implemented, and the experiment and accuracy analysis were carried out using large-scale actual data. The results show that the method can help improve the ratio of estimating alighting stops effectively, and the accuracy ratio reached 87.90%. This can be used in practical work of public transportation planning and management.

参考文献/References:

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[12]陈君,杨东援.基于APTS数据的公交卡乘客通勤OD分布估计方法[J].交通运输系统工程与信息,2013,13(4):47-53.


CHEN Jun, YANG Dongyuan. Method of estimating smart card commuters OD distribution based on APTS data[J]. Journal of Transportation Systems Engineering and Information Technology, 2013, 13(4):47-53.

相似文献/References:

[1]陈君,杨东援,赵清梅.公交线路选择的相关性规律和换乘总量计算模型[J].西安建筑科技大学学报(自然科学版),2017,49(06):835.[doi:10.15986/j.1006-7930.2017.06.010]
　CHEN Jun,YANG Dongyuan,ZHAO Qingmei.Correlation law for bus routes selection and total transfer volume calculation model[J].J. Xi’an Univ. of Arch. & Tech.(Natural Science Edition),2017,49(01):835.[doi:10.15986/j.1006-7930.2017.06.010]

备注/Memo

备注/Memo:
收稿日期:2017-01-02修改稿日期:2018-01-10

基金项目:国家自然科学基金项目（51208408）;陕西省自然科学基础研究计划项目（2017JM5121）； 陕西省教育厅专项科研计划项目（17JK0461）

第一作者:陈君（1977-），男，副教授，博士，主要从事城市交通规划与管理研究. E-mail:chenjuntom@126.com
更新日期/Last Update: 2018-03-15