Abstract
Despite the 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, however, 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 in order to identify the determinants thereof and direct the policies towards appropriate population groups. In view of this, the main contribution of this proposed 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 will be estimated on an open dataset acquired from a stated preferences survey in the U.S.
Description
Timeline
Strategic Description / RD&T
Page 17 of the USDOT's RD&T Plan: Table 3: "Data-driven System Safety"
Deployment Plan
Research has deployment potential in informing policy decisions.
Expected Outcomes/Impacts
The expected outcome of this research project is the capability enhancement in modeling the public acceptance behavior of the autonomous vehicle (AV) technology, which is a crucial input to directing proactive policy interventions towards appropriate population groups in order to promote the adoption of AVs.
The anticipated impacts of this research project are 1) improved technology in informing policy decisions regarding whether and how the public would be concerned about the AV safety and its effect on the public acceptance of AVs; and 2) enlargement of the pool of trained transportation professionals at the nexus of transportation safety and travel behavior.
Expected Outputs
The anticipated output of this research project includes a state-of-the-art econometric method implemented on an open stated preferences (SP) dataset.
TRID
Over the past decade, there has been a growing interest in analyzing the transportation system landscape with the emergence of autonomous vehicle (AV) technology. On the demand side, several aspects of the users’ response behavior to AVs were explored, which encompass a process starting with inquiring a sample of individuals’ about their general opinion about whether, when, how, and why they accept AVs, and subsequently relating the individuals’ responses (as outcome variables) to their socio-demographic characteristics, current travel behavior, trip attributes, as well as their concerns and attitudes (as explanatory variables). A review of the relevant literature reveals the presence of two major research gaps. First, a clear behavioral understanding is lacking as to the public’s 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 joint econometric model with ordinal-continuous outcome variables will be presented and estimated in this project.
Individuals Involved
| Email |
Name |
Affiliation |
Role |
Position |
| fatemeh.nazari@utrgv.edu |
Nazari, Fatemeh |
University of Texas - Rio Grande Valley |
PI |
Faculty - Untenured, Tenure Track |
| h.noruzoliaee@utrgv.edu |
Noruzoliaee, Mohamadhossein |
University of Texas - Rio Grande Valley |
Co-PI |
Faculty - Untenured, Tenure Track |
Budget
Amount of UTC Funds Awarded
$43720.00
Total Project Budget (from all funding sources)
$76719.88
Documents
Match Sources
No match sources!
Partners
| Name |
Type |
| City of Edinburg |
Deployment & Equity Partner Deployment & Equity Partner |
