United States Department of Transportation
i
On the Role of Perceived Safety Concerns on Public Acceptance Behavior of Autonomous Vehicles
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2024-07-30
[PDF-988.69 KB]
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Corporate Contributors:Carnegie Mellon University. Traffic21 Institute. Safety21 University Transportation Center (UTC) ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology ; United States. Department of Transportation. Federal Highway Administration
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Edition:Final Report (July 1, 2023-June 30, 2024)
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Abstract:Despite maturing road tests and limited commercial mobility services with autonomous vehicles (AVs), the existing behavioral research, surveys, and polls suggest that, to date, the public is largely reluctant or neutral to accept this emerging technology due to potential lurking failures and malfunctions in unexpected weather/road conditions and cyber-attacks. The persistence of this demand landscape for AVs could curb the promising economic, societal, and environmental benefits of prevalent autonomous mobility. Proactive policy interventions are thus much needed early on to provide impetus for AV acceptance, which should be informed by an in-depth understanding of the AV acceptance behavior of the public to identify the determinants thereof and direct the policies towards appropriate population groups. In view of this, the main contribution of this project is advancing this knowledge through a joint econometric modeling framework to unravel the impact on AV acceptance of individuals’ perceived concern about AV safety, among other influential factors, while at the same time “endogenously” connecting the perceived safety concern to the individuals’ characteristics and attitudinal profiles. Notably, the joint modeling framework can disentangle the “true” interdependencies between AV safety concern and AV acceptance from the effect of any unobserved factors that commonly influence both AV safety concern and AV acceptance behavior (i.e., endogeneity effects). Accommodating the endogeneity issue could help avoid inconsistent estimation results and in turn misleading policy recommendations. Moreover, since AV acceptance behavior is related to household vehicle decisions, the public latent preferences for vehicle attributes (e.g., vehicle cost, reliability, performance, and refueling) will also be accounted for. The proposed model is estimated on an open dataset acquired from a stated preferences survey in the U.S.
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