  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.
