Passenger Time Use Comparison Between Traditional and Autonomous Vehicles: A Latent Class and Transition Analysis

Abstract

As the era of autonomous vehicles (AVs) approaches, understanding how passengers’ time use during a trip may change from a traditional vehicle (non-AV) to an AV is important to the adoption and use of AVs. In this study, a latent class analysis (LCA) as well as a latent transition analysis (LTA) are adopted to investigate the choice of travel activities of individuals as passengers in a traditional vehicle, such as a car or transit, and the anticipated shift in these activities in an AV. Since individuals may perform different activities during different trip purposes, activity choices and non-AV to AV transition dynamics are explored from two different perspectives: commute trips (e.g., to work or school) and non-commute trips (e.g., leisure, errands, or medical). Findings from the LCA models show three distinct groups of individuals with varying activity preferences in a traditional vehicle and four distinct groups that could emerge in an AV. AV users exhibited a higher preference for activities such as texting/browsing social media, relaxing, and working, suggesting that AVs may offer passengers a more productive use of their travel time. Furthermore, the LTA model shows that there is a good portion of individuals who were performing one or two activities in a traditional vehicle now becoming variety seekers that could perform at least four different activities in an AV, further corroborating the findings that AVs could provide a more productive and efficient use of travel time.