Citation

Hardman S, Lee JH, Tal G. Transp. Res. A Policy Pract. 2019; 129: 246-256.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.tra.2019.08.008

PMID

unavailable

Abstract

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.

Language: en

Keywords

Automated vehicle; Behavior; Electric vehicle; Use; Vehicle miles travelled