Journal of Transportation Systems Engineering and Information Technology ›› 2019, Vol. 19 ›› Issue (1): 132-137.

• Systems Engineering Theory and Methods • Previous Articles     Next Articles

Influence Mechanism of School Commuting Pattern Using Metro Smart Card Data

LIU Yang1, JI Yan-jie1, HE Min2, GU Yu1   

  1. 1. School of Transportation, Southeast University, Nanjing 211189, China; 2. Faculty of Transportation Engineering, Kunming University of Science & Technology, Kunming 650051, China
  • Received:2018-08-09 Revised:2018-09-19 Online:2019-02-25 Published:2019-02-25

基于地铁刷卡数据的通学模式影响机理研究

刘阳 1,季彦婕*1,何民 2,顾宇 1   

  1. 1. 东南大学 交通学院,南京 211189;2. 昆明理工大学 交通工程学院,昆明 650051
  • 作者简介:刘阳(1990-),女,云南昆明人,博士生.
  • 基金资助:

    国家自然科学基金/National Natural Science Foundation of China(51561135003, 51338003);东南大学优秀博士学位论文培育基金/ Scientific Research Foundation of Graduated School of Southeast University(YBJJ1842).

Abstract:

Long-distance school commuting is a key factor that lead to the car trips needed for school escorting of primary and secondary school students. Encouraging students who have a middle or long travel distance between home and school commute by metro can reduce their dependence on household cars. Considering that the students who use metro for one- way trips are potential to be escorted by their parents, this paper explored the school commuting patterns of primary and secondary school students by using the three-week metro smart card data. By identifying the school metro commuters and their commuting trips, students’metro commuting behavior is divided into four patterns. Further, the factors affecting school commuting patterns are identified based on multivariate Logistic regression model. The results show that the student's departure time, travel frequency, residential location, school location and built environment have significant impacts on the metro school commuting. Meanwhile, the impacts of built environment near home and that near school are different on student' s school commuting patterns.

Key words: urban traffic, school commuting pattern, multivariate Logistic regression model, medium and long distance, smart card data, metro

摘要:

长距离的通学出行是导致中小学生被家长用小汽车接送的关键因素,鼓励中长距离通学学生使用地铁出行可以减少他们对小汽车的依赖.本文在考虑潜在接送行为的基础上,利用地铁IC卡刷卡数据研究了南京市中小学生的地铁通学模式.通过识别出地铁通学人群及对应的通学记录,把学生地铁通学行为分为只去不回 (HTSO)、只回不去 (STHO)、往返 (SHUTTLE)和其他(OTHERS)模式,并建立多元Logistic模型分析了学生出行特征、所在区位、居住地及学校周边建成环境特征对其地铁通学模式的影响.模型结果显示,学生的出发时刻、出行频率、居住地区位、学校区位及建成环境对地铁通学模式有显著影响,且居住地和学校周边建成环境对学生通学模式的影响不同.

关键词: 城市交通, 通学模式, 多项Logistic回归模型, 中长距离, 刷卡数据, 地铁

CLC Number: