How does the built environment affect interest in the ownership and use of self-driving vehicles?
Connected and automated (self-driving) vehicles (CAVs and AVs) will soon become a viable mode option, though their exact pattern of adoption and use is expected to vary based on consumer interests and concerns about the technology. Past work has shown the rate at which AVs are implemented depends on several factors, such as individual and household demographics and technology costs (Bansal and Kockelman, 2017; Lee et al., 2017; Daziano et al., 2017). This research analyzes another group of attributes that help predict how people will purchase and use AVs: land use characteristics. Here, the results of two large-scale preference surveys are used to estimate how land use characteristics impact Americans’ perceptions of, interest in, and willingness to pay for AV technology, while controlling for demographic attributes. Both surveys were conducted in 2017 and together represented over 4000 U.S. households.Statistical models like the ordered probit and multinomial logit are used to estimate the impacts of demographics and land use characteristics on AV-related behavior. Various land use variables arise as significant depending on the question being asked of the respondents. For example, poor job accessibility via automobile is associated with higher levels of interest in AVs, higher anticipated use of AV technology, a willingness-to-pay (WTP) for self-driving capability, and a greater reliance on AVs for some long-distance travel.This research provides metrics of practical (and statistical) significance of a suite of land use variables, relative to common demographic predictors, to identify for planners, engineers, policymakers, and others where the most rapid AV deployments will occur first.
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- © 2019 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
- Nodjomian, Adam T
- Kockelman, Kara
- Publication Date: 2019-6
- Media Type: Web
- Features: Appendices; Photos; References; Tables;
- Pagination: pp 115-134
- TRT Terms: Attitudes; Automobile ownership; Autonomous vehicles; Built environment; Connected vehicles; Land use; Multinomial logits; Probits
- Subject Areas: Highways; Planning and Forecasting; Vehicles and Equipment;
- Accession Number: 01712015
- Record Type: Publication
- Files: TRIS
- Created Date: Jun 1 2019 3:05PM