Day-to-Day Travel Variability in the Commute Atlanta, Georgia, Study
Day-to-Day Travel Variability in the Commute Atlanta, Georgia, Study
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佐治亚州亚特兰大通勤的日常出行变化研究
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
Jennifer Ogle
中科院分区：
文献类型：
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作者：
V. Elango;R. Guensler;Jennifer Ogle
传统的旅行日记调查从参与者家庭收集1到2天的旅行数据。虽然横断面旅行日记调查在确定区域人口的总体平均旅行行为方面很有用，但它对家庭内部和个人内部旅行的可变性提供的洞察很少。纵向调查通常是检查旅行可变性的首选方法。这项研究的目的是检查佐治亚州亚特兰大通勤研究中的家庭内部出行变异性，这是一项基于全球定位系统的仪表式车辆监测研究，收集了260个有代表性的家庭约500辆车的车辆出行情况。这项研究工作使用了2004年为通勤亚特兰大研究收集的旅行数据，其中一个家庭旅行次数的平均变异性或偏差为每天3次。人口变量(例如，家庭规模、家庭收入、车辆拥有量、子女数量、工作人员数量和学生数量)显著影响每天家庭出行总次数的日常变化。通过分别分析春季、夏季和秋季特定月份的旅行数据，可以控制由于季节性影响而产生的变异性。结果表明，如果剔除与季节性影响相关的变异性，人口变量对家庭出行次数的日常变异性有显著影响。被参与者确定为经常或偶尔用于商务或商业目的的车辆的出行模式与其他车辆不同，它们在样本中的存在将严重影响纵向数据分析的分析结果。商业用车被排除在出行变异性分析之外，在未来的出行日记数据收集和纵向研究中，必须将拥有商业用车的家庭作为一个独立的样本对待。
Traditional travel diary surveys collect 1 or 2 days of travel data from participant households. Although useful in determining the overall average travel behavior of a regional population, cross-sectional travel diary surveys provide little insight into intrahousehold and intraperson trip variability. Longitudinal surveys are generally preferred for examining travel variability. The objective of the research is to examine the intrahousehold travel variability in the Commute Atlanta, Georgia, study, a Global Positioning System–based instrumented-vehicle monitoring study that collected vehicle trips from approximately 500 vehicles in 260 representative households. The research effort uses 2004 travel data collected for the Commute Atlanta study, in which the average variability or deviation in the number of trips by a household was 3 trips/day. Demographic variables (e.g., household size, household income, vehicle ownership, number of children, number of workers, and number of students) significantly affect the day-to-day variability in the total number of household trips per day. The variability due to seasonal effects is controlled by separately analyzing travel data during specific months in spring, summer, and fall. Results indicate that demographic variables have a significant effect on the day-to-day variability of the household number of trips when the variability associated with seasonal effects is excluded. Vehicles identified by participants as being used always or occasionally for business or commercial purposes have travel patterns different from those of other vehicles, and their presence in the sample will significantly bias analytical results in the analysis of longitudinal data. Commercial use vehicles are excluded from travel variability analysis, and the argument is made that households with such vehicles must be treated as an independent sample in future travel diary data collection and longitudinal studies.