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Do People Prefer Cars That People Don’t Drive? A Survey Study on Autonomous Vehicles
- Source :
- Energies, Vol 14, Iss 16, p 4795 (2021)
- Publication Year :
- 2021
- Publisher :
- MDPI AG, 2021.
-
Abstract
- Only recently, smart cities are taking shape, thanks to the rapid development of Internet of Things (IoT), cloud computing, and other similar technologies. Given the high demands placed on advanced technologies such as autonomous driving, cloud data services, and high-precision sensors, smart cities are creating an intelligent transportation environment conducive to the introduction of autonomous vehicles (AVs). In this context, the use of AVs in transportation is also considered a form of transportation innovation. As a result, AVs are considered more favorable to people interested in new technologies because they appear to be technologically superior. Their association with the most up-to-date technology can serve as a symbol for those who wish to demonstrate their interest in new technologies through their appearance. The positive image of technological innovation projected by AVs may influence their acceptance among technology enthusiasts to a significant degree. In this context, this study investigates the effects of perceived advantage, perceived risk, and perceived safety on the intention to use autonomous vehicles. For this purpose, data were collected from vehicle users living in Turkey by survey method. Secondly, factor analyses and regression analyses were performed with the data set obtained from 611 participants. As a result of the analyses, it has been determined that the perceived advantage and perceived security increase the intention to use autonomous vehicles. In contrast, the perceived risk reduces this intention to use. According to these results, recommendations were made to the companies about the level of acceptance of this technology by the users to assess their investments in autonomous vehicles better.
Details
- Language :
- English
- ISSN :
- 14164795 and 19961073
- Volume :
- 14
- Issue :
- 16
- Database :
- Directory of Open Access Journals
- Journal :
- Energies
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.0ffa60f2c416450d90c22158835d7b2b
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/en14164795