[1]陈 红,李晨光,刘 爽,等.考虑群体差异的地铁出行时空特征及影响因素[J].长安大学学报(自然科学版),2025,45(01):114-124.[doi:10.19721/j.cnki.1671-8879.2025.01.010]
　CHEN Hong,LI Chen-guang,LIU Shuang,et al.Spatio-temporal characteristics and influencing factors of subway travel considering group differences[J].Journal of Chang’an University (Natural Science Edition),2025,45(01):114-124.[doi:10.19721/j.cnki.1671-8879.2025.01.010]
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考虑群体差异的地铁出行时空特征及影响因素()
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长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
第45卷
期数:
2025年01期
页码:
114-124
栏目:
交通工程
出版日期:
2025-02-28

文章信息/Info

Title:
Spatio-temporal characteristics and influencing factors of subway travel considering group differences
文章编号:
1671-8879(2025)01-0114-11
作者:
陈 红; 李晨光; 刘 爽; 刘恩泽; 姚振兴
(长安大学 运输工程学院,陕西 西安 710064)
Author(s):
CHEN Hong;  LI Chen-guang;  LIU Shuang;  LIU En-ze;  YAO Zhen-xing
(School of Transportation Engineering, Chang'an University, Xi'an 710064, Shaanxi, China)
关键词:
交通工程;  城市交通;  轻量级梯度提升机;  群体差异;  建成环境;  老年人
Keywords:
traffic engineering;  urban traffic;  LightGBM;  group difference;  built environment;  elderly
分类号:
U491.17
DOI:
10.19721/j.cnki.1671-8879.2025.01.010
文献标志码:
A
摘要:
为分析地铁站点周边建成环境对不同年龄群体出行时空特征的影响,以西安市为例,结合手机信令数据、兴趣点数据和土地利用数据,提取老年群体和非老年群体的轨道交通客流量及4类建成环境变量。对出行时空特征进行深入分析的基础上,使用轻量级梯度提升机(LightGBM)探讨地铁站点周边建成环境对不同群体客流量的特征重要度和非线性影响。研究结果表明:LightGBM模型在拟合和预测不同年龄群体出行特征方面表现出优异的效果,显著优于传统的梯度提升决策树(GBDT)模型和线性回归(LR)模型; 老年群体早晚高峰呈双峰形,老年群体无明显峰值; 2类群体地铁出行距离主要集中在7～20 km,活动范围主要位于西安市三环内,但三环外热门景区附近的地铁站点吸引了大量非老年群体; 建成环境因素对2类群体地铁出行的影响重要度存在差异,交通相关特征是影响2类群体地铁客流量最重要的特征,对老年群体的影响大于非老年群体,居住人口密度和工作人口密度对老年群体的影响小于非老年群体; 医疗中心数量、科教文化数量、公司企业数量、公交站点密度与2类群体客流量呈非线性正相关,且有明显的阈值效应,当医疗中心数量达到58、科教文化数量为48时,促进作用最明显。研究结果对构建老年友好型城市体系具有重要意义,为制定增强老年人出行能力的相关政策提供参考。
Abstract:
To analyze the impact of the built environment around metro stations on spatio-temporal travel characteristics for different groups, Xi'an was conducted as an example, mobile signaling data, points of interest(POI)data and land use data were integrated to extract metro ridership for elderly and non-elderly groups, along with four categories of built environment variables.Based on an in-depth analysis of spatio-temporal travel characteristics, the light gradient boosting machine(LightGBM)was applied to explore the feature importance and nonlinear effects of the built environment around metro stations on ridership for different groups.The results show that the LightGBM model outperforms traditional gradient boosting decision tree(GBDT)models and linear regression(LR)models in fitting and predicting travel characteristics.The elderly group exhibits a bimodal distribution during morning and evening peak hours, whereas no distinct peak is observed for the non-elderly group. The travel distance for both groups predominantly ranges between 7 to 20 km, with activity areas mainly located within the third ring road of Xi'an. However, metro stations near popular attractions outside the third ring road attract a significant number of non-elderly passengers.The importance of built environment factors on metro ridership varies between the two groups. Transportation-related features are the most significant factors influencing both groups, with a greater impact on the elderly group compared to the non-elderly group. Residential population density and employment density have a lesser impact on the elderly group than the non-elderly group. The number of medical centers, educational and cultural facilities, companies, and bus stop density are positively correlated with ridership for both groups, showing clear threshold effects. Specifically, the number of medical centers has the most pronounced effect at 58, while educational and cultural facilities have the greatest impact at 48.These findings are crucial for building an age-friendly urban system and provide valuable insights for formulating policies to enhance the mobility of the elderly.6 tabs, 8 figs, 26 refs.

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备注/Memo

备注/Memo:
收稿日期:2024-09-11
基金项目:国家自然科学基金项目(52002030)
作者简介:陈 红(1963-),女,湖南湘潭人,教授,博士研究生导师,E-mail:glch@chd.edu.cn。
通讯作者:姚振兴(1989-),男,浙江金华人,副教授,工学博士,E-mail:yaotraffic@chd.edu.cn。
更新日期/Last Update: 2025-02-25