An empirical investigation on consumers’ intentions towards autonomous driving

Major steps towards implementation of autonomous and connected transport are being taken nowadays. The trend of automation technology being used in vehicles by the most important vehicle manufacturing industries is expected to move closer to high or fully Autonomous Vehicles (AVs) through technological advancements in sectors of robotics and artificial intelligence. Vehicles with autonomous driving capabilities are planning to be available on market, in full scale, in the next years. In the longer term substantial benefits are mainly expected for accessibility to transport, safety, traffic flow, emissions, fuel use and comfort. All these potential societal benefits will not be achieved unless AVs are accepted and used by a critical mass of people. Addressing these challenges, this paper: (a) proposes a technology acceptance modelling process by extending the original Technology Acceptance Model (TAM) to explain and predict consumers’ intensions towards AVs, (b) based on the proposed TAM-extended framework, a 30-question survey was conducted in order to investigate the factors influencing consumers’ intensions to use and accept AVs. Results show that the constructs of perceived usefulness, perceived ease to use, perceived trust and social influence, are all useful predictors of behavioral intentions to have or use AVs, with perceived usefulness having the strongest impact. The insights derived from this study could significantly contribute to ongoing research related to technology acceptance of AVs and are expected to allow automobile industries to improve their design and technology.

• Record URL:
  https://doi.org/10.1016/j.trc.2018.08.013
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0968090X1830086X
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • © 2018 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Panagiotopoulos, Ilias
  • Dimitrakopoulos, George
• Publication Date: 2018-10

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 773-784
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 95
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Acceptance; Automobile travel; Consumer behavior; Intelligent vehicles; Psychological trust
• Uncontrolled Terms: Intentions
• Subject Areas: Data and Information Technology; Economics; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01682075
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 27 2018 4:10PM