Assessing the Impact of Driver Experience and Cybersecurity Concerns on Public Trust in Autonomous Vehicles

The rapid advancement of artificial intelligence and automation has led to significant developments in autonomous vehicle technology. However, public trust remains a crucial factor influencing the adoption and widespread acceptance of self-driving cars. This study explores the relationship between driver experience, cybersecurity concerns, and trust in autonomous vehicles, aiming to identify key factors that shape consumer perception.

Existing research highlights that familiarity with emerging technologies positively impacts trust, while cybersecurity threats are often cited as a major barrier to adoption. However, empirical evidence on how these factors interact remains inconclusive. This paper investigates whether individuals with a driver’s license exhibit greater confidence in autonomous vehicles and whether concerns about cyberattacks significantly reduce trust.

A quantitative research methodology was employed, using a structured survey distributed to 530 respondents. Three hypotheses were tested through statistical analysis, including the Spearman’s rank correlation test and the Mann-Whitney U test. The results indicate a strong positive correlation between familiarity with autonomous vehicles and trust in their ability to reduce accidents. Furthermore, individuals with a driver’s license were found to have significantly higher trust levels than those without. Surprisingly, cybersecurity concerns did not exhibit a meaningful correlation with trust in autonomous vehicles, suggesting that public perception is shaped more by exposure and experience than by theoretical risks.

This research contributes to the field of artificial intelligence applications in business and mobility by providing empirical evidence on the psychological and experiential factors influencing trust in autonomous vehicles. The research findings bring to the forefront the need for educational campaigns and hands-on exposure programs aimed at increasing public confidence, especially among people who do not have a driving license. The information this study reveals can help policy makers and impact automotive companies and technology developers, providing support in increasing public acceptance and integration of autonomous vehicles into modern transportation systems.