Original Research ARTICLE
Predictors of Attitudes towards Autonomous Vehicles: The Roles of Age, Gender, Prior Knowledge, and Personality
- 1Florida State University, United States
- 2Purdue University, United States
Autonomous vehicles (AVs) hold considerable promise for maintaining mobility in older adults developing impairments in driving skill. Nonetheless, attitudes can be a significant barrier to adoption as has been shown for other technologies. We investigated how different introductions to AV, video with a driver in the front seat, the rear seat, and a written description, affected attitudes, as well as how individual difference variables such as age, gender, prior knowledge, and personality traits predict attitudes within a middle-aged (Median age = 34, IQR = 20, n=441) Amazon Mechanical Turk sample. The 16-item attitude survey uncovered three factors: Concern with AV, Eagerness to Adopt AV technology, and Willingness to Relinquish Driving Control. ANOVAs showed that only age (younger less concerned) and gender, (females more concerned) were significant factors in Concern with AV. Only gender affected Willingness to Relinquish Driving Control, with males more willing. Multiple regressions that included previous knowledge level and personality traits showed a different pattern. Female gender and greater conscientiousness were associated with greater Concern about AV. Prior knowledge of AV was associated with less concern. Emotional stability and openness to experience were positive predictors of Eagerness to Adopt AV, whereas conscientiousness was a negative predictor. Prior knowledge and openness to experience, positively, and extraversion, negatively, were associated with being willing to relinquish driving control. These results suggest that different information dissemination campaigns are needed to persuade consumers to adopt AV technology. We discuss potential approaches.
Keywords: Autonomous vehicle (AV), age, gender, Personality, knowledge, attitudes, Technology
Received: 26 Jun 2018;
Accepted: 03 Dec 2018.
Edited by:Mike Murphy, University College Cork, Ireland
Reviewed by:Ariel Telpaz, General Motors (United States), United States
Michael Cooke, Maynooth University, Ireland
Copyright: © 2018 Charness, Yoon, Souders, Stothart and Yehnert. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Prof. Neil Charness, Florida State University, Tallahassee, 32306, Florida, United States, firstname.lastname@example.org
Ms. Courtney Yehnert, Florida State University, Tallahassee, 32306, Florida, United States, email@example.com