Graduation Semester and Year

2018

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Urban Planning and Public Policy

Department

Urban and Public Affairs

First Advisor

Shima Hamidi

Second Advisor

Diane Jones Allen

Third Advisor

Maria Martinez-Cosio

Abstract

Although the self-driving technology promises to solve several urban issues, the deployment of the autonomous vehicles (AV) is an evolutionary process that depends on different factors. One of these factors is the public adoption of AVs that plays a crucial role in the deployment of this technology by controlling the level of market penetration. By analyzing the cross-national survey studies on AVs acceptance, the author finds that the rate of AVs adoption in America is considerably lower than other developed countries. Although some studies have focused on the AVs adoption in the US and the factors that affect it, there is little evidence regarding the role of built environment on acceptance of driver-less cars. However, previous studies prove the impact of built environmental elements on different travel modes (walking driving and using transit). Therefore, there might be a link between built environment and public adoption of driverless cars as an innovative travel mode. This dissertation addresses this knowledge gap by surveying residents of the Dallas-Fort Worth (DFW) metropolitan area and measuring built environmental factors around each respondent and analyzing how these factors influence the acceptance rate. To test the hypothesis of the research, the author designs a survey about the AVs adoption and different sociodemographic, travel preference and travel behavioral factors that influence public adoption in DFW. The author creates a half-mile network buffer around each respondent’s location and measures built environmental within each buffer. Then the author statistically analyzes the effects of built environmental and socio-demographic features on people’s perception towards shared and private autonomous vehicles. The findings of the analysis exposed the substantial impact of built environmental factors on the public adoption of shared autonomous vehicles. Living in more accessible neighborhoods increases the likelihood of adopting shared autonomous vehicles and residents of these areas are willing to pay more for this technology. Moreover, neighbourhood accessibility increases the chance of accepting private autonomous vehicle although its effect is not significant. Besides built environment, other factors that significantly affect SAVs adoption are gender (male), disabilities (that prevent driving), technology-familiarity factor (includes having a post-graduate education, being tech-savvy, experiences of using car-sharing services and driver assistant features), and non-driving travel preference (walking, biking, and using transit). Therefore, male residents, having disabilities, familiar with technology, with non-driving travel preference, and living in accessible neighborhoods, are features of the individuals who are likely to use shared driverless car services. Moreover, factors that significantly affect public adoption of private autonomous cars are age, gender (male), travel preference, and technology familiarity. Therefore, male residents, young individuals, people with high technology familiarity, and people who prefer non-driving travel modes are more likely to purchase private autonomous vehicles. The findings also emphasize the low rate of AVs acceptance in the DFW area that is aligned with the other U.S. cities. Around 47% of respondents show interest to shop for a driver-less car, 35% adopt using a shared autonomous car, and totally 54% accept either private or shared autonomous cars. Moreover, educating survey participants about the technology increases the adoption rate to 63%.

Keywords

Autonomous vehicles, Public adoption, Transportation planning, Built environment

Disciplines

Architecture | Urban, Community and Regional Planning

License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Comments

Degree granted by The University of Texas at Arlington

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