Advancing Transportation Equity and Safety Through Autonomous Vehicles
- PMID: 38505763
- PMCID: PMC10949946
- DOI: 10.1089/heq.2023.0107
Advancing Transportation Equity and Safety Through Autonomous Vehicles
Abstract
Motor vehicle crashes are a leading cause of death in the United States, and disproportionately impact communities of color. Replacing human control with automated vehicles (AVs) holds the potential to reduce crashes and save lives. The benefits of AVs, including automated shuttles, buses, or cars could extend beyond safety to include improvements in congestion, reductions in emissions, and increased access to mobility, particularly for vulnerable populations. However, AVs have not attained the level of public trust that has been expected, given their potential to save lives and increase access to mobility. Public opinion surveys have highlighted safety and security concerns as reasons for this lack of confidence. In this study, we present the findings of an experiment we conducted to actively shift mindsets on AVs toward advancing health equity. We demonstrate through a nationally representative sample of 2265 U.S. adults that the public support for AVs can be improved by expanding their scope of application to include advancing social benefit. The survey began with questions on respondent's support for AVs based on a priori knowledge and beliefs. Consistent with prior surveys, baseline support (strong support and some degree of support) was low at 26.4% (95% confidence interval 24.0-29.0). After introducing information about how AVs could be used to provide mobility for older adults, those with limited income, or the vision-impaired, respondents were asked to reassess their support for AVs. Support significantly increased to include the majority of respondents. By prioritizing the deployment of AVs to serve individuals and communities in greatest need of mobility, AVs would not only demonstrate compelling social value by reducing disparities but would also gain widespread public support among the U.S. public.
Keywords: autonomous vehicles; public support; social benefit.
© Johnathon P. Ehsani et al., 2024; Published by Mary Ann Liebert, Inc.
Conflict of interest statement
No competing financial interests exist.
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References
-
- National Center for Statistics and Analysis. Early Estimate of Motor Vehicle Traffic Fatalities in 2021. National Highway Traffic Safety Administration: Washington, DC; 2022.
-
- Yellman MA. Motor vehicle crash deaths—United States and 28 other high-income countries, 2015 and 2019. MMWR Morb Mortal Wkly Rep 2022;71(26);837–843. - PubMed
-
- Marshall WE, Ferenchak NN. Assessing equity and urban/rural road safety disparities in the US. J Urban Int Res Placemaking Urban Sustain 2017;10(4):422–441.
-
- Governors Highway Safety Association. An Analysis of Traffic Fatalities by Race and Ethnicity. GHSA: Washington DC; 2021.
-
- Nordhoff S, van Arem B, Happee R. Conceptual model to explain, predict, and improve user acceptance of driverless podlike vehicles. Transport Res Rec 2016;2602(1):60–67; doi: 10.3141/2602-08 - DOI
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