  With the prospect of next-generation automated mobility ecosystem, the
realization of the contended traffic efficiency and safety benefits are
contingent upon the demand landscape for automated vehicles (AVs). Focusing on
the public acceptance behavior of AVs, this empirical study addresses two gaps
in the plethora of travel behavior research on identifying the potential
determinants thereof. First, a clear behavioral understanding is lacking as to
the perceived concern about AV safety and the consequent effect on AV
acceptance behavior. Second, how people appraise the benefits of enhanced
automated mobility to meet their current (pre-AV era) travel behavior and
needs, along with the resulting impacts on AV acceptance and perceived safety
concern, remain equivocal. To fill these gaps, a recursive trivariate
econometric model with ordinal-continuous outcomes is employed, which jointly
estimates AV acceptance (ordinal), perceived AV safety concern (ordinal), and
current annual vehicle-miles traveled (VMT) approximating the current travel
behavior (continuous). Importantly, the co-estimation of the three endogenous
outcomes allows to capture the true interdependencies among them, net of any
correlated unobserved factors that can have common impacts on these outcomes.
Besides the classical socio-economic characteristics, the outcome variables are
further explained by the latent preferences for vehicle attributes (including
vehicle cost, reliability, performance, and refueling) and for existing shared
mobility systems. The model estimation results on a stated preference survey in
the State of California provide insights into proactive policies that can
popularize AVs through gearing towards the most affected population groups,
particularly vehicle cost-conscious, safety-concerned, and lower-VMT (such as
travel-restrictive) individuals.
