TY - JOUR
T1 - How do drivers use automation? Insights from a survey of partially automated vehicle owners in the United States
AU - Hardman, Scott
AU - Lee, Jae Hyun
AU - Tal, Gil
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/11
Y1 - 2019/11
N2 - In this study we investigate how partially automated vehicles (Tesla electric vehicles with “Autopilot”) are used, including how often automation is used, on what roads, in what weather, and in what traffic conditions. We use a latent class model to identify heterogenous classes of autopilot users, then we use a multinomial logistic regression model to understand the relationship between each latent class and several independent variables, including socio-demographics and vehicle miles travelled (VMT). The latent class model revealed four latent classes: very frequent users, who use it most frequently; frequent users, who use automation frequently in clear weather and on freeways; semi-frequent users who use it for less than half their trips and only on freeways, in clear weather, when there is no traffic; and infrequent users, who use it the least often and only in clear weather, on freeways, when there is no traffic. The multinomial logistic regression model revealed significant differences in VMT between the clusters. Very frequent and Frequent users drive close to 15,000 miles per year, whereas Semi frequent and Infrequent users drive around 10,000 miles per year. The results suggest that consumers who purchase partially automated vehicles and use them frequently may travel more.
AB - In this study we investigate how partially automated vehicles (Tesla electric vehicles with “Autopilot”) are used, including how often automation is used, on what roads, in what weather, and in what traffic conditions. We use a latent class model to identify heterogenous classes of autopilot users, then we use a multinomial logistic regression model to understand the relationship between each latent class and several independent variables, including socio-demographics and vehicle miles travelled (VMT). The latent class model revealed four latent classes: very frequent users, who use it most frequently; frequent users, who use automation frequently in clear weather and on freeways; semi-frequent users who use it for less than half their trips and only on freeways, in clear weather, when there is no traffic; and infrequent users, who use it the least often and only in clear weather, on freeways, when there is no traffic. The multinomial logistic regression model revealed significant differences in VMT between the clusters. Very frequent and Frequent users drive close to 15,000 miles per year, whereas Semi frequent and Infrequent users drive around 10,000 miles per year. The results suggest that consumers who purchase partially automated vehicles and use them frequently may travel more.
KW - Automated vehicle
KW - Behavior
KW - Electric vehicle
KW - Use
KW - Vehicle miles travelled
UR - http://www.scopus.com/inward/record.url?scp=85071294371&partnerID=8YFLogxK
U2 - 10.1016/j.tra.2019.08.008
DO - 10.1016/j.tra.2019.08.008
M3 - Article
AN - SCOPUS:85071294371
SN - 0965-8564
VL - 129
SP - 246
EP - 256
JO - Transportation Research Part A: Policy and Practice
JF - Transportation Research Part A: Policy and Practice
ER -