标题： 代际差异在汽车使用中的表现：使用梯度提升决策树比较美国千禧一代和X世代 显示英文标题

标题： Generational Differences in Automobility: Comparing America's Millennials and Gen Xers Using Gradient Boosting Decision Trees

摘要： 千禧一代是否比前几代人更少以汽车为中心在文献中得到了广泛讨论。 大多数现有研究使用回归模型，并假设所有因素在导致年轻成年人驾驶行为方面都是线性相加的。 本研究通过应用非参数统计学习方法，即梯度提升决策树（GBDT），放松了这一假设。 利用美国2001年和2017年的全国出行调查数据，本研究考察了生命周期、社会人口和居住因素对千禧一代和X世代年轻成年人每日驾驶距离的非线性剂量反应效应。 在保持其他所有因素不变的情况下， 千禧一代的年轻成年人的预测每日驾驶距离比他们的X世代同龄人短。 此外，居住和经济因素解释了大约50%的年轻成年人的每日驾驶距离，而生命周期事件和人口统计学的集体贡献约为33%。 本研究还确定了制定有效土地利用政策以减少汽车出行需求的密度范围。 显示英文摘要

摘要： Whether the Millennials are less auto-centric than the previous generations has been widely discussed in the literature. Most existing studies use regression models and assume that all factors are linear-additive in contributing to the young adults' driving behaviors. This study relaxes this assumption by applying a non-parametric statistical learning method, namely the gradient boosting decision trees (GBDT). Using U.S. nationwide travel surveys for 2001 and 2017, this study examines the non-linear dose-response effects of lifecycle, socio-demographic and residential factors on daily driving distances of Millennial and Gen-X young adults. Holding all other factors constant, Millennial young adults had shorter predicted daily driving distances than their Gen-X counterparts. Besides, residential and economic factors explain around 50% of young adults' daily driving distances, while the collective contributions for life course events and demographics are about 33%. This study also identifies the density ranges for formulating effective land use policies aiming at reducing automobile travel demand.