基于自动售检票数据的地铁换乘站换乘时间分析

doi:10.16097/j.cnki.1009-6744.2025.06.016

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (6): 175-184.DOI: 10.16097/j.cnki.1009-6744.2025.06.016

基于自动售检票数据的地铁换乘站换乘时间分析

刘晨辉^*a,b，陶梦鑫^a

湖南大学，a.土木工程学院；b.综合交通研究中心，长沙410082

收稿日期:2025-09-17 修回日期:2025-10-09 接受日期:2025-10-16 出版日期:2025-12-25 发布日期:2025-12-24
作者简介:刘晨辉(1987—)，男，山东济宁人，教授，博士。
基金资助:
湖南省自然资源厅科技计划项目 (HBZ20240122)；中央高校基本科研业务费专项资金(5311180)。

Exploration of Transfer Time at Metro Transfer Stations with Automatic Fare Collection Data

LIU Chenhui^*a,b, TAO Mengxin^a

a. College of Civil Engineering; b. Transportation Research Center, Hunan University, Changsha 410082, China

Received:2025-09-17 Revised:2025-10-09 Accepted:2025-10-16 Online:2025-12-25 Published:2025-12-24
Supported by:
Science and Technology Plan Project of the Department of Natural Resources of Hunan Province (HBZ20240122)；Fundamental Research Funds for the Central Universities of Ministry of Education of China (5311180)。

摘要/Abstract

摘要： 换乘是制约城市轨道交通系统服务水平的重要因素，而明确分析城市轨道交通换乘时间是制定有效提升策略的前提。以长沙市地铁为研究对象，基于历史1周的AFC(Automatic Fare Collection)数据，对换乘时间进行深入分析。首先，构建换乘次数受限的广度优先搜索算法，识别最短换乘路径，进一步分解乘客出行链时间结构，建立线性回归模型，采用最小二乘法估计参数，从而量化换乘时间；接着，从空间分布、时间变化和相对耗时这3个维度对换乘时间进行客观全面的分析。结果表明，长沙市地铁平均换乘时间为6.2 min，占总出行时间的17.6%，工作日换乘耗时高于休息日，且存在高峰时段换乘效率退化现象。空间分布上，不同换乘站点之间存在一定差异，进一步利用K-means算法进行聚类分析，7座通道换乘站点被识别为低效率站点。基于研究结果，提出采用物理结构优化、实时引导和互联互通等措施，提升地铁换乘效率。

关键词: 城市交通, 换乘时间, K-means聚类分析, 城市轨道交通, 自动售检票

Abstract: Transfer efficiency is a key factor affecting the service quality of urban rail transit systems, and analysis on transfer time is essential to develop effective improvement strategies. This study investigates the transfer time based on the Automated Fare Collection (AFC) data of Changsha Metro system in one week. A breadth-first search (BFS) algorithm with transfer-count constraints was developed to identify shortest transfer paths. Based on the identified trips, a linear regression model was constructed, and parameters were estimated by using the ordinary least squares (OLS) method to quantify transfer times. Transfer characteristics were analyzed from three perspectives: spatial distribution, temporal variation, and relative duration within the entire trip. The results show that the average transfer time in Changsha Metro is 6.2 minutes, accounting for 17.6% of the total travel time. Transfer times on weekdays are generally longer than that on weekends, with noticeable efficiency degradation during peak hours. In terms of spatial distribution, significant differences exist among transfer stations, and K-means clustering was further applied to classify stations by transfer performance. Seven transfer stations with passageway-type layouts were identified as low-efficiency nodes. Based on the findings, this paper proposes optimization strategies including structural improvements, real time passenger guidance, and inter-line interoperability to improve the transfer efficiency in metro system.

Key words: urban traffic, transfer time, K-means clustering analysis, urban rail transit, Automated Fare Collection (AFC)

中图分类号:

U231.4

刘晨辉, 陶梦鑫. 基于自动售检票数据的地铁换乘站换乘时间分析[J]. 交通运输系统工程与信息, 2025, 25(6): 175-184.

LIU Chenhui, TAO Mengxin. Exploration of Transfer Time at Metro Transfer Stations with Automatic Fare Collection Data[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(6): 175-184.

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http://www.tseit.org.cn/CN/Y2025/V25/I6/175

参考文献

[1]韩宝明,李卓一,靳雨馨,等.2024年世界城市轨道交通运营统计与分析综述[J].都市快轨交通,2025,38 (1): 1-12. [HAN B M, LI Z Y, JIN Y X, et al. Statistical analysis of urban rail transit operations worldwide in 2024: a review[J]. Urban Rapid Rail Transit, 2025, 38(1): 1-12.]

[2] 中国城市轨道交通协会.城市轨道交通2023年度统计和分析报告[R/OL]. (2024-03-29) [2025-09-06]. https://www.camet.org.cn/xytj/tjxx/14894.shtml. [China Association of Metros. Urban rail transit 2023 annual statistics and analysis report[R/OL]. (2024-03-29) [2025-09-06]. https://www.camet.org.cn/xytj/tjxx/14894. shtml.]

[3]发展改革委.国家发展改革委关于印发“十四五”新型城镇化实施方案的通知[R/OL]. (2022-06-21) [2025 09-06]. https://www.gov.cn/zhengce/zhengceku/2022 07/12/content_5700632.htm. [National Development and Reform Commission. Notice on issuing the '14th Five Year Plan' new urbanization implementation plan[R/OL]. (2022-06-21) [2025-09-06]. https://www.gov.cn/ zhengce/zhengceku/2022-07/12/content_5700632.htm.]

[4]杜鹏,刘超,刘智丽.地铁通道换乘乘客走行时间规律研究[J]. 交通运输系统工程与信息,2009, 9(4): 103 109. [DU P, LIU C, LIU Z L. Walking time modeling on transfer pedestrians in subway passages[J]. Journal of Transportation Systems Engineering and Information Technology, 2009, 9(4): 103-109.]

[5] 王宇辰,李小雅,张媛雅,等.基于主观评价法的地铁换乘满意度调查:以北京地铁为例[J].现代城市轨道交通, 2025(1): 103-109. [WANG Y C, LI X Y, ZHANG Y Y, et al. A survey on metro transfer satisfaction based on subjective evaluation method: A case study of Beijing metro[J]. Modern Urban Transit, 2025(1): 103-109.]

[6]钱堃,陈垚,毛保华.考虑换乘时间影响的城市轨道交通路径选择行为研究[J].交通运输系统工程与信息, 2015, 15(2): 116-121. [QIAN K, CHEN Y, MAO B H. Route choice behavior for urban rail transit considering transfer time[J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15(2): 116-121.]

[7]陈培文,秦国栋.重庆市城市轨道交通网络化运营客流特征分析[J]. 城市交通,2025,23(3): 108-113. [CHEN P W, QIN G D. Passenger flow characteristics of Chongqing rail transit network[J]. Urban Transport of China, 2025, 23(3): 108-113.]

[8]朱国,章澜岚,刘家俊,等.基于多源数据的城市轨道交通乘客路径选择估计方法[J].都市快轨交通,2025, 38(1): 99-105. [ZHU G, ZHANG L L, LIU J J, et al. Estimation method of urban rail transit passenger route choices based on multi-source data[J]. Urban Rapid Rail Transit, 2025, 38(1): 99-105.]

[9] 许明,王锁平,刘毅.城市轨道交通乘客出行路径精准分析算法研究[J].城市轨道交通研究,2023,26(5):55 58, 64. [XU M, WANG S P, LIU Y. Research on accurate analysis algorithm of urban rail transit passenger travel path[J]. Urban Mass Transit, 2023, 26(5): 55-58, 64.]

[10] 蒋黎, 包佳瑶,高明,等.城市轨道交通换乘站位置对乘客换乘路径选择的影响[J]. 城市轨道交通研究, 2024, 27(4): 56-60. [JIANG L, BAO J Y, GAO M, et al. Influence of urban rail transit interchange station location on passenger interchange route selection[J]. Urban Mass Transit, 2024, 27(4): 56-60.]

[11] 杨骐畅, 成子龙,吴奇,等.基于K-Means聚类分析的长沙市常规公交与轨道交通竞合关系研究[J].市政技术, 2024, 42(5): 138-144, 219. [YANG Q C, CHENG Z L, WU Q, et al. Research on the coopetition relationship between bus transit and rail transit in Changsha City based on K-Means cluster analysis[J]. Journal of Municipal Technology, 2024, 42(5): 138-144, 219.]

[12] 刘晨辉,邓洁榕,刘令.基于LDA的城市轨道交通客流节假日出行模式研究[J/OL].湖南大学学报(自然科学版). (2025-06-13) [2025-09-06]. https://link.cnki.net/ urlid/43.1061.N.20250613.1416. 004. [LIU C H, DENG J R, LIU L. Research on holiday travel patterns in urban rail transit based on LDA[J/OL]. Journal of Hunan University (Natural Sciences), (2025-06-13)[2025-09 06]. https://link. cnki.net/ urlid/43.1061.N.20250613. 1416.004.]

[13] 邓洁榕,刘晨辉.基于GMM模型的城市轨道交通乘客通勤模式研究:以长沙市为例[J]. 都市快轨交通, 2025, 38(3): 48-53. [DENG J R, LIU C H. Exploration of travel patterns of urban rail transit commuters based on gaussian mixture model (GMM): A case study of Changsha, China[J]. Urban Rapid Rail Transit, 2025, 38 (3): 48-53.]

[14] 朱宇婷,戎亚萍,赵欣苗.换乘效率对城市轨道交通分担率的影响研究[J].交通运输系统工程与信息,2017, 17(2): 35-40. [ZHU Y T, RONG Y P, ZHAO X M. Impact of transfer efficiency on the market share of urban rail transit[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(2): 35-40.]

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基于自动售检票数据的地铁换乘站换乘时间分析

Exploration of Transfer Time at Metro Transfer Stations with Automatic Fare Collection Data

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