ISSN 1789-8919
e-ISSN 2786-1562
The application of artificial intelligence (AI) in the autonomous vehicle market has shown significant growth between 2017 and 2024. This study aims to answer the following research question through secondary data analysis: To what extent have artificial intelligence technologies—specifically machine learning, deep learning, and computer vision—contributed to trends and innovations in the autonomous vehicle market during the chosen period? I explored the role of AI technologies in the development of autonomous systems by conducting a comprehensive analysis of the IEEE, Scopus and further relevant databases publications to the topic.
The results show that machine learning algorithms have significantly improved the perception and pattern recognition capabilities of autonomous vehicles, enabling accurate classification of traffic signs and reliable detection of pedestrians. Deep learning techniques have facilitated the processing of complex environmental data, supporting the development of computer vision and 3D environment modeling. Sensor fusion and AI-based real-time decision-making have played a key role in improving vehicle reliability and efficiency, contributing to market growth.
The integration of AI technologies has not only been a driver of vehicle technology development, but has also influenced industry trends, regulatory frameworks, and facilitated the emergence of intelligent transportation systems. I found that AI has significantly contributed to innovations and trends in the autonomous vehicle market between 2017 and 2024. I conclude that AI technologies will continue to be a driver of autonomous vehicle development, and I recommend further research on the integration of AI and smart city infrastructures, as well as addressing regulatory and ethical challenges.
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