Autonomous vehicle adoption behavior and safety concern: A study of public perception

Realizing the economic and societal benefits of autonomous vehicles (AVs) hinges on widespread public acceptance. However, existing research offers limited insights into two key behavioral factors shaping AV acceptance, namely, perceived AV safety concern and travel behavior, the latter reflecting how heterogenous mobility patterns influence the AV acceptance. These factors are often treated as exogenous, limiting insight into their true behavioral interdependencies with AV acceptance and their distinct behavioral roots. This study addresses these gaps by introducing a recursive trivariate econometric model that jointly estimates AV acceptance, perceived safety concern, and current travel behavior (proxied by annual vehicle-miles traveled or VMT). The recursive structure accounts for structural endogeneity, enabling the unbiased estimation of how safety concern and travel behavior influence AV acceptance, while treating both as endogenous constructs shaped by their own determinants. To further enhance behavioral realism, the model incorporates latent psychological constructs using structural equation modeling. Empirical results from a California stated preference dataset highlight that safety concern and latent vehicle cost consciousness are the two dominant deterrents to AV acceptance, suggesting that policies such as trust-building campaigns and financial incentives can stimulate AV acceptance. Despite showing less safety concern, high-VMT individuals exhibit lower AV acceptance, suggesting potential habitual inertia in ceding driving control and challenging conjectures that users embrace in-vehicle saving and that AVs promote urban sprawl. Shared mobility enthusiasm and latent vehicle performance preference alleviate AV safety concern. Gender and racial gaps persist, with women expressing greater safety concerns and Asians exhibiting higher AV acceptance.