Adoption of partially automated vehicle technology features and impacts on vehicle miles of travel (VMT)

Abstract

In this paper, we examine vehicle owners’ adoption of five different types of partially automated features (PAFs); lane keeping system, backup camera (BUC), adaptive cruise control (ACC), automatic braking system (ABS), and blind spot monitoring; as well as PAF effects on vehicle miles of travel (VMT). The joint modeling of PAF adoption and VMT is achieved using both individual demographic characteristics as well as psycho-social characteristics. A Generalized Heterogeneous Data Model (GHDM) is estimated, which controls for possible self-selection effects in PAF adoption based on VMT, and thus is able to provide “true” PAF effects on VMT. Our analysis specifically indicates that ignoring this self-selection can lead to a significant underestimation of the VMT increase due to PAF adoption. The results also indicate that women and older individuals (65 years or older) appear to be more inclined to invest in assistive PAFs, because of a perception that these assistive features still leave the human driver in control. However, women are less likely than men to invest in the more active ABS PAF because of heightened safety concerns with technology. In terms of PAF effects on VMT, PAFs focusing on lateral movement assistance appear to have a smaller VMT effect than those that serve longitudinal movement assistance. The highest estimated VMT change of 2,462 miles (13.8% change) is for the case when the package of BUC, ACC, and ABS is installed for middle-aged men. The highest percentage VMT change (40%), though, is for the same package of BUC, ACC, and ABS for older women. Overall, there are considerable variations in VMT impact across demographic groupings, suggesting that a single aggregate percentage improvement in safety benefits may suffer from the well-known ecological fallacy.