Privacy on Autopilot: Exploring User Attitudes Toward Data Use in Autonomous Vehicles

The rapid evolution of autonomous vehicle (AV) technology driven by artificial intelligence (AI) and big data analytics is transforming the landscape of modern transportation. Yet, this technological progress brings pressing concerns about data privacy and user trust, particularly due to the constant collection, sharing, and analysis of real-time data. This study explores user perceptions of data privacy in autonomous vehicles, with a focus on the context of Dubai. Utilizing machine learning (ML) techniques and k-fold cross-validation, we analyzed user data across various demographic factors, including age, gender, and education, to accurately predict privacy concerns. Among several classifiers K-Nearest Neighbors, Decision Tree, Support Vector Machine (SVM), Random Forest, Neural Networks, and AdaBoost Gradient Boosting demonstrated the highest predictive accuracy. The results underscore the importance of robust data governance frameworks, public awareness initiatives, and cross-sector collaboration among policymakers, AI researchers, and the automotive industry. Future work should consider longitudinal studies, the application of advanced deep learning models, and the development of comprehensive regulatory strategies to foster a privacy-conscious, AI-enabled mobility ecosystem.