The Future on Wheels: A joint heterogeneous model of automated vehicle adoption and perceived employment and economic impacts

Automated Vehicles (AVs) offer solutions to many urban challenges but also pose complex social and economic issues. This study evaluates the American public’s perceptions of how the widespread adoption of AVs might affect income disparities. We further hypothesize that such perceptions are intertwined with concerns about AV impacts on employment (ride-hailing, ridesharing, and delivery driver jobs) and individuals’ affinity to use AVs. Using a national survey of 4,631 Americans, we present a rigorous behavioral model to jointly analyze these interconnected endogenous outcomes while accounting for recursive (structural) effects and unobserved heterogeneity in the impacts of exogenous factors. Among surveyed Americans, including those willing to use AVs, approximately 85% believe AVs will disrupt driving-related employment, and 47% believe they will exacerbate income disparities. We identify a range of sociodemographic, behavioral, ideological, and spatial determinants of AV use and perceived economic impacts. Clear patterns of social, digital, and geographic divides are observed. Despite considerable heterogeneities, some groups (e.g., those aware of AVs, frequent internet users, more educated individuals, and self-identified liberals) are open to adopting AVs but remain concerned about potential economic impacts, whereas others (e.g., lower-income, residents of non-metropolitan areas, and those for whom religion is important) are both apprehensive of potential adverse impacts and generally unwilling to use AVs. Treatment effects are simulated to identify policy measures to increase public acceptance while mitigating potential adverse societal impacts. Findings suggest that, beyond traditional strategies to boost acceptance, deliberate and proactive policies are needed to address perceived economic concerns. This can help ensure an equitable deployment of AVs that fosters public trust. Results call for a broad-based socio-technical approach to AV deployment, considering social, geographic, and technical landscapes to ensure AVs benefit all societal segments. Our findings will be of interest to policymakers, engineers, and planners.