Factors Affecting Autonomous Vehicles Adoption: A Systematic Review, Proposed Framework, and Future Roadmap

Abstract

Autonomous vehicles (AVs) offer several benefits, such as improving road safety, mitigating traffic congestion, and reducing fuel consumption and gas emissions. Despite these benefits, their adoption rate remains limited due to various factors influencing users’ decisions. While previous studies have identified numerous factors influencing AV adoption using various adoption frameworks, the factors have not been comprehensively analyzed and synthesized. Thus, this systematic review aims to bridge this gap by identifying and classifying the factors influencing the adoption of AVs. Out of 3,532 collected research papers, 71 empirical studies were analyzed thoroughly. The findings demonstrated that the technology acceptance model (TAM) was the most widely used model for investigating AV adoption. The identified factors in the analyzed studies were classified into distinct categories: psychological and behavioral factors, technological factors, social factors, environmental factors, security and privacy factors, AV-related factors, risky and negative factors, conditional factors, and monetary factors. We have proposed an AV adoption framework grounded in this taxonomy to direct subsequent empirical research. We have also highlighted numerous agendas to serve as a blueprint for future AV adoption studies. This review offers various theoretical insights and actionable recommendations for multiple AV research, development, and implementation stakeholders.

Keywords:

• Drivers
• barriers
• autonomous vehicles
• technology adoption
• systematic review
• future roadmap

Data availability

The data presented in this study are available on request from the authors.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Saeed Al Mansoori

Saeed Al Mansoori is the Director of the Remote Sensing Department at Mohammed Bin Rashid Space Centre (MBRSC). He is currently pursuing his PhD degree in Computer Science at The British University in Dubai. Saeed’s research interests include HCI, signal and image processing, artificial intelligence, remote sensing, GIS, etc.

Mostafa Al-Emran

Mostafa Al-Emran is an Assistant Professor at The British University in Dubai. He is among the top 2% scientists worldwide, according to the studies published by Stanford University in October 2020, 2021, 2022, and 2023. He has over 135 publications, including journal articles, books, conferences, book chapters, and editorials.

Khaled Shaalan

Khaled Shaalan, a distinguished Computer Science Professor with three decades in academia, excels in teaching, mentoring, curriculum development, and academic leadership. As Computer Science Department Head, he pioneered its growth, expanded research teams, and fostered global collaborations. His extensive publications and evaluation expertise make him a sought-after figure in academia.