Activity Pattern Choice of Work Commuting Trip by Workers
-
摘要: 用基于活动的出行需求理论分析出行行为,建立了工作者通勤出行活动模式选择行为模型.采用多项Logistic方法研究了1 695个样本的个体特征和家庭特征对4种典型出行模式(HWH+,HW+WH,HWHWH,HWH)选择行为的影响,其中HWH+表示上下班途中有其他停留,HW+WH表示工作中外出(不含回家)并返回单位,HWHWH表示工作中回家并返回单位,HWH表示工作中无外出模式.结果表明,以HWH为参照,女性及家庭工作人数多的个体较多选择HWH+模式;私营及个体职业者、受教育程度高及有驾照的个体较多选择HW+WH模式;工人、服务员、职员以及年龄40岁以上、家庭中高收入、居住在中心区的个体较多选择HWHWH模式.
-
关键词:
- 通勤出行 /
- 活动模式 /
- 多项Logistic回归模型 /
- 发生比率
Abstract: Models describing activity patterns of work commuting trips by workers were established based on activity-based travel demand analysis theory.Multinomial logistic method was adopted to analyze the effects of socio-demographics of individuals/households on their choices of four typical activity patterns,i.e.,HWH+,HW+WH,HWHWH and HWH,where HWH+ is defined as the trip with at least one additional stop for a nonwork activity,HW+WH means that there is at least one short leave for a nonwork activity during working time,HWHWH at least a short leave for home during working time,and HWH presents that there is not any other activity during working time.The analysis indicates that,compared to HWH,females and households with more working members are prone to choose the HWH+ pattern;the self-employed and those with higher education and with driving licenses prefer the HW+WH pattern;and blue/white collar workers and employees in service trade,as well as those over 40 years old,with high family income and dwelling in downtowns,are more likely to chose the HWHWH pattern.-
Key words:
- commuting trip /
- activity pattern /
- multinomial Logistic regression model /
- odds ratio
-
陈学武.可持续发展的城市交通系统模式研究[D].南京:东南大学,2002.[2] WALLACE B.TDM policy implications of the characteristics of commute and non-commute trip chains[EB/CD].The 80th Annual Meeting of the Transportation Research Board,Washington,D.C.:[s.n.],2001:1-10.[3] BOWMAN J L,BEN-AKIVA M.Activity-based disaggregate travel demand model system with activity schedules[J].Transportation Research,Part A,2000,35(1):1-28.[4] KITAMURA R,CHEN C,Micro-simulation of daily activity-travel patterns for travel demand forecasting[J].Transportation,2000,27(2):25-51.[5] BHAT C R.A comprehensive and operational analysis framework for generating the daily activity-travel pattern of workers[EB/CD].The 79th Annual Meeting of the Transportation Research Board,Washington,D.C.:[s.n.],2000:1-34.[6] KASTURIRANGAN K,PENDYALA R M,A comparation of commuter activity scheduling and sequencing behavior across geographical contexts[EB/CD].The 80th Annual Meeting of the Transportation Research Board,Washington,D.C.:[s.n.],2001:1-28.[7] 褚浩然,郑猛,杨晓光,等.出行链特征指标的提出及应用研究[J].城市交通,2006,4(2):64-67.CHU Haoran,ZHENG Meng,YANG Xiaoguang,et al.A study on trip-chain indices and their application[J].Urban Transport of China.2006,4(2):64-67.[8] 李志瑶,隽志才,宗芳.居民出行时间选择及拥挤收费政策[J].交通运输工程学报,2005,5(3):105-110.LI Zhiyao,JUAN Zhicai,ZONG Fang.Resident travel time choice and congestion pricing policy[J].Journal of Traffic and Transportation Engineering,2005,5(3):105-110.[9] 高歌,张明芝.多分类有序反应变量Logistic回归及其应用[J].同济大学学报,2003,31(10):1237-1241.GAO Ge,ZHANG Mingzhi.Polytomous logistic regression for ordinal response and it's appliance[J].Journal of Tongji University.2003,31(10):1237-1241[10] 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,2001:1-145.[11] 关宏志.非集计模型——交通行为分析的工具[M].北京:人民交通出版社,2004:26-60.[12] 张文彤.SPSS11统计分析教程[M].北京:北京希望电子出版社,2002:91-121.
点击查看大图
计量
- 文章访问数: 1686
- HTML全文浏览量: 55
- PDF下载量: 680
- 被引次数: 0