基于地铁刷卡数据的通学模式影响机理研究
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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.
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.
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.
引文
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[2]ZHANG R,YAO E,LIU Z.School travel mode choice in Beijing,China[J].Journal of Transport Geography,2017(62):98-110.
[3]何保红,刘阳,何民.通勤制约度对儿童陪伴出行决策过程的影响[J].交通运输系统工程与信息,2014,14(6):223-30.[HE B H,LIU Y,HE M.Influence of commuter constraints degree on children accompany travel decision-making process[J].Journal of Transportation Systems Engineering&Information Technology,2014,14(6):223-230.]
[4]LIU Y,JI Y J,SHI Z B,et al.Investigating the effect of the spatial relationship between home,workplace and school on parental chauffeurs'daily travel mode choice[J].Transport Policy,2018(69):78-87.
[5]余柳,刘莹.北京市小学生通学交通特征分析及校车开行建议[J].交通运输系统工程与信息,2011,11(5):193-199.[YU L,LIU Y.Traffic characteristics analysis and suggestions on school bus operation for primary school students in Beijing[J].Journal of Transportation Systems Engineering&Information Technology,2011,11(5):193-200.]
[6]MITRA R,BULIUNG R N.The influence of neighborhood environment and household travel interactions on school travel behavior:an exploration using geographically-weighted models[J].Journal of Transport Geography,2014,36(2):69-78.
[7]MA X,ZHANG J Y,DING C,et al.A geographically and temporally weighted regression model to explore the spatiotemporal influence of built environment on transit ridership[J].Computers Environment&Urban Systems,2018(70):113-124.
[8]龙瀛,张宇,崔承印.利用公交刷卡数据分析北京职住关系和通勤出行[J].地理学报,2012,67(10):1339-1352.[LONG Y,ZHANG Y,CUI C Y.Identifying commuting pattern of Beijing using bus smart card data[J].Acta Geographica Sinica,2012,67(10):1339-1352.]
[9]王济川,郭志刚.Logistic回归模型:方法与应用[M].北京:高等教育出版社,2001.[WANG J C,GUO Z G.Logistic regression model:Methods and application[M].Beijing:Higher Education Press,2001.]
[10]马书红,韩亚慧,姚志刚,等.基于父母出行特性的学生出行方式选择研究[J].交通运输系统工程与信息,2016,16(2):225-231.[MA S H,HAN Y H,YAO Z G,et al.Students'travel mode choice based on parents travel mode[J].Journal of Transportation Systems Engineering&Information Technology,2016,16(2):225-231.]