Shared autonomous vehicles and their potential impacts on household vehicle ownership: An exploratory empirical assessment

Menon, Nikhil; Barbour, Natalia; Zhang, Yunlong; Pinjari, Abdul Rawoof; Mannering, Fred

doi:10.1080/15568318.2018.1443178

Cited by 156 publications

(82 citation statements)

References 39 publications

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“…The results of these prior studies consistently suggest that (i) there is considerable positive interest in AVs in the community (Bansal, Kockelman, & Singh, 2016;Menon et al, 2016;Payre, Cestac, & Delhomme, 2014;Schoettle & Sivak, 2014); (ii) males, younger people, and those with higher levels of education are likely to express greater interest in using AVs (Dong, DiScenna, & Guerra, 2017;Hohenberger et al, 2016;König & Neumayr, 2017;Lavieri et al, 2017;Menon, Barbour, Zhang, Pinjari, & Mannering, 2018;Nielsen & Haustein, 2018;Payre et al, 2014;Regan et al, 2017;Schoettle & Sivak, 2014); and (iii) there are substantial sections of the population that would not be prepared to pay any extra for full vehicle automation (Daziano, Sarrias, & Leard, 2017;Kyriakidis, Happee, & de Winter, 2015;Regan et al, 2017;Schoettle & Sivak, 2014). The main perceived advantages of AVs appear to be accident reduction, increased mobility for vulnerable people, and greater leisure time, while the primary anticipated problems relate to equipment failure and safety issues, followed by hacking and liability issues (Bansal et al, 2016;König & Neumayr, 2017;Kyriakidis et al, 2015;Menon et al, 2016;Regan et al, 2017).…”

Section: Introductionmentioning

confidence: 90%

Dimensions of attitudes to autonomous vehicles

Pettigrew

Worrall

Talati

et al. 2019

Urban, Planning and Transport Research

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For the benefits of autonomous vehicles (AVs) to be optimized, the fleet conversion process needs to be efficient and timely. This study explored public attitudes to AVs to inform strategies to increase receptivity to the wide-scale use of AVs. A national online survey was administered to a sample of 1,624 Australians aged 16+ years. The survey featured open-ended questions that scoped respondents' perceptions of AVs. A grounded, thematic analysis identified two primary dimensions in the data: response valence (how positive or negative the comments were about the advent of AVs) and response type (the extent to which the comments reflected a cognitive or emotional response). This resulted in a dimensional analysis featuring four quadrants that captured the topics that were most frequently raised spontaneously by respondents. The quadrant characterized by comments that were positive/neutral and cognitive in nature was the most substantial, indicating general acceptance. Where concerns were expressed, they typically related to perceived safety, trust, and control issues, and tended to be more emotional in nature. The results highlight the importance of providing the public with concrete information about AVs to address fear levels and to resolve trust and control issues.

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Section: Introductionmentioning

confidence: 90%

Dimensions of attitudes to autonomous vehicles

Pettigrew

Worrall

Talati

et al. 2019

Urban, Planning and Transport Research

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“…AV technology has received considerable attention in major car manufacturers and IT companies. Under the background of the sharing economy, the advent of AV technology will bring a novel mobility pattern such as SAV, which could transform vehicles from an owned product to an on-demand service [3][4][5]. SAVs can drive to pick up passengers autonomously without moving to a waiting spot.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Factors Affecting Mode Choice Intention of Autonomous Vehicle Based on an Extended Theory of Planned Behavior—A Case Study in China

et al. 2019

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Autonomous vehicle (AV) is an innovative transport option that has the potential to disrupt all industries tied to transportation systems. The advent of AV technology will bring a novel on-demand mobility pattern such as shared autonomous vehicle (SAV). To promote AV technology, it is important to understand which factors influence travelers’ intention to use AVs and SAVs. This paper collected literature from databases such as Scopus, Web of Science and ScienceDirect, and made a systematic review. The study aims to explore the determinants that influence travelers’ behavioral intentions towards use AVs and SAVs based on an extended version of the theory of planned behavior, which incorporates knowledge and perceived risk. This study was tested empirically using a valid survey sample collected from 906 respondents in China. Structural equation model was conducted to investigate the predictors of intentions to use AVs and SAVs. Results showed that knowledge about AV technology and perceived risk are the two main potential obstacles for travelers to use AVs and SAVs. Attitude significantly affects AVs and SAV choice intentions. Subjective norm is the most critical factor affecting the travelers' intention to use AVs. Perceived behavioral control potentially stymie the travelers' intention to use SAVs. The findings will enhance the understanding of travelers’ choice motivation from psychological and service perspectives, and provide data support for governments and companies in improving travel management strategies and product services.

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“…Some studies have started to explore changes in vehicle ownership or residential location (e.g. Carrese et al, 2019;Menon et al, 2019). These societal shifts may produce the greatest implications for future transportation planning/policy.…”

Section: Introductionmentioning

confidence: 99%

Will autonomous vehicles change residential location and vehicle ownership? Glimpses from Georgia

Kim

Circella

2020

Transportation Research Part D: Transport and Environment

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Many studies have begun investigating possible transportation landscapes in the autonomous vehicle (AV) era, but empirical results on longer-term decisions are limited. We address this gap using data collected from a survey designed and implemented for Georgia residents in 2017-2018. Focusing on a hypothetical all-AV future, this section of the survey included questions regarding advantages/disadvantages of AVs, short-term mode choice impacts, mediumterm impacts on activity patterns, and long-term behavioral changes-specifically, whether/how AVs will influence individuals to change residential location and the number of cars in the household. We hypothesize that AVs could act in concert with attitudinal preferences to stimulate changes in these long-term decisions, and that some medium-term activity changes triggered by AVs could motivate people to relocate their residence or shed household vehicles. We applied exploratory factor analysis to measure the perceived likelihood that AVs would prompt various medium-term changes. We then included some of those measures, among other variables, in a cross-nested logit (CNL) model of the choice of the residential location/vehicle ownership bundle. Although more than half of respondents expected "no change" in their bundle, we found that younger, lower income, pro-suburban, and pro-non-car-mode individuals were more likely to anticipate changing their selections. In addition, some expected medium-term impacts of AVs influenced changes in these longer-term choices. We further applied the CNL model to two population segments (Atlanta and non-Atlanta-region residents). We found notable improvement in goodness of fit and different effects of factors across segments, signifying the existence of geography-related taste heterogeneity.

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Shared autonomous vehicles and their potential impacts on household vehicle ownership: An exploratory empirical assessment

Cited by 156 publications

References 39 publications

Dimensions of attitudes to autonomous vehicles

Dimensions of attitudes to autonomous vehicles

Exploring the Factors Affecting Mode Choice Intention of Autonomous Vehicle Based on an Extended Theory of Planned Behavior—A Case Study in China

Will autonomous vehicles change residential location and vehicle ownership? Glimpses from Georgia

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