Examining motivations for owning autonomous vehicles: Implications for land use and transportation
Illustrating the associations between built environment characteristics and autonomous vehicle (AV) ownership helps policymakers understand where AVs emerge first and their impacts on society. However, few studies have addressed interest in AV ownership from the spatial perspective. Using regional travel survey data from the Twin Cities, the authors applied the gradient boosting decision tree method to test three hypotheses (diffusion of innovation, efficiency, and modal substitution) underlying the relationships between respondents' interest in owning AVs and its correlates. Results showed that the innovation-diffusion hypothesis dominates the motivations for owning AVs, followed by preference for efficiency and then modal substitution. However, its associations with built environment variables suggest more of preference for efficiency than of diffusion of innovation and modal substitution. Population density, road connectivity, and land use entropy are negatively associated with the interest. The results provide suggestions to address the externalities of AVs in different areas.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/09666923
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Supplemental Notes:
- © 2022 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
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Authors:
- Tao, Tao
- Cao, Jason
- Publication Date: 2022-6
Language
- English
Media Info
- Media Type: Web
- Features: Appendices; Figures; References; Tables;
- Pagination: 103361
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Serial:
- Journal of Transport Geography
- Volume: 102
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0966-6923
- Serial URL: http://www.elsevier.com/locate/jtrangeo
Subject/Index Terms
- TRT Terms: Automobile ownership; Autonomous vehicles; Built environment; Innovation; Land use; Modal shift; Population density
- Subject Areas: Highways; Planning and Forecasting; Vehicles and Equipment;
Filing Info
- Accession Number: 01850812
- Record Type: Publication
- Files: TRIS
- Created Date: Jun 30 2022 9:42AM