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Intrapersonal day-to-day travel variability and duration of household travel surveys: Moving beyond the one-day convention
Journal of Transport and Land Use ( IF 1.6 ) Pub Date : 2018-11-26 , DOI: 10.5198/jtlu.2018.984
Wei Li , Douglas Houston , Marlon G. Boarnet , Han Park

By analyzing seven-day travel logs from Los Angeles during 2011–2013, we contribute to the understanding of intrapersonal day-to-day travel variability (IDTV) in relation to socio-demographic and land-use characteristics and the implication of travel survey duration for travel parameter estimates. Our main sample included 2,395 person-days from 352 individual participants in 219 households. Our analytical methods included linear regressions and random sampling experiments. Our Feasible Generalized Least Squares (FGLS) regression models revealed that many factors significantly influenced IDTV, such as gender, age, income, and household type. However, the observed socio-demographic and land-use characteristics could only explain a small portion of IDTV. The random sampling experiments enabled us to contrast travel variables measured from the seven-day master sample with those from subsamples of a shorter period (one to six days). The “optimal” duration for a travel survey may depend on the specific travel variables measured, and we provide evidence that studies of transit and non-motorized travel will require longer surveys than studies of car travel. In conclusion, the conventional one-day approach is likely to produce imprecise parameter estimates due to the intrapersonal day-to-day travel variability. We recommend that transportation professionals and policy makers consider shifting from the conventional one-day approach toward a multi-day approach. Surveys that focus on the modes of walking, biking, and transit should consider data collection for at least seven days.

中文翻译:

个人日常旅行差异和家庭旅行调查的持续时间:超越一日公约

通过分析2011-2013年洛杉矶的7天旅行日志,我们有助于了解个人的日常旅行变异性(IDTV)与社会人口统计学和土地使用特征的关系,以及旅行调查持续时间的影响用于旅行参数估计。我们的主要样本包括来自219个家庭的352个个人参与者的2,395人日。我们的分析方法包括线性回归和随机抽样实验。我们的可行广义最小二乘(FGLS)回归模型显示,许多因素显着影响IDTV,例如性别,年龄,收入和家庭类型。但是,观察到的社会人口和土地利用特征只能解释IDTV的一小部分。随机抽样实验使我们能够将从7天主样本测得的旅行变量与较短时期(一到六天)的子样本的旅行变量进行对比。旅行调查的“最佳”持续时间可能取决于所测量的特定旅行变量,我们提供的证据表明,对过境和非机动旅行的研究比对汽车旅行的研究需要更长的调查时间。总之,由于个人内部日常旅行的可变性,传统的一日行方法可能会产生不精确的参数估计。我们建议运输专业人士和政策制定者考虑从传统的一日制过渡到一日制。重点关注步行,骑自行车和过境方式的调查应考虑至少收集7天的数据。
更新日期:2018-11-26
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