Assessing automated vehicle-induced VMT: meta-analysis of current research

Abstract

Automated Vehicles (AVs) are rapidly transforming the transportation landscape. It is crucial to understand the impact of AVs on vehicle miles traveled (VMT), a key metric of travel behavior. Despite numerous systematic literature reviews, there is a lack of robust statistical analysis on this topic. This study fills this gap with a multivariate meta-analysis of 26 published articles, providing 195 effect sizes of AVs’ impact on VMT in U.S. cities and metropolitan areas. The analysis reveals a 5.95% increase in VMT for shared and non-shared AVs combined. Individually, shared automated vehicles (SAVs) show a 5.3% increase, while non-shared AVs demonstrate a greater increase of 6.9% in VMT. Additionally, a moderator variable analysis identifies factors influencing the impact of AVs on VMT, helping to explain variations in specific study outcomes. Among thirteen moderator variables, four significantly affect VMT. The results indicate that while AV deployment generally leads to increased VMT, higher operating costs and higher value of travel time (VOTT) can negatively impact VMT increase. In contrast, system speed, AV penetration rate, average travel time, and average trip distance positively influence the effect. In summary, AV deployment is anticipated to lead to an overall increase in VMT, with a greater impact observed for non-shared AVs compared to shared AVs. These findings provide valuable insights for policymakers and urban planners aiming to balance the benefits and potential drawbacks of AV technology in shaping future transportation systems.