  The objective of this study is to investigate automated vehicle (AV) adoption
perceptions, including ownership intentions and the willingness to use
self-driving mobility services. In this paper, we use data from the 2018
California Transportation Survey, and use K-means, a clustering technique in
data mining, to reveal patterns of potential AV owners (and non-owners) as well
as AV users (and non-users) of self-driving services. The results reveal seven
clusters, namely Multitaskers/ environmentalists/ impaired drivers, Tech
mavens/ travelers, Life in transition, Captive car-users, Public/ active
transport users, Sub-urban Dwellers, and Car enthusiasts. The first two
clusters include adopters who are largely familiar with AVs, are tech savvy,
and who make good use of time during their commute. The last cluster comprise
of non-adopters who are car enthusiasts. On the other hand, people who are Life
in transition, Captive car-users, Public/ active transport users, and Sub-urban
dwellers show uncertain perceptions towards being AV adopters. They are either
pursuing higher education, having a busy schedule, supporting for sustainable
society via government policies, or have a stable life, respectively. Insights
from this study help practitioners to build business models and strategic
planning, addressing potential market segments of individuals that are willing
to own an AV vs. those that are more inclined to use self-driving mobility
services. The "gray" segments identify a latent untapped demand and a potential
target for marketing, campaigns, and sales.
