The Impact of Artificial Intelligence on Passenger Flow in Air and Rail Integrated Networks: A Systematic Literature Review

Integrating air and rail transportation systems offers a significant opportunity to enhance global mobility and operational efficiency. This study explores the role of Artificial Intelligence (AI) in addressing passenger behaviour and interoperability in air-rail networks. Advanced AI techniques are employed to analyse passenger behaviour patterns and optimize multimodal integration. Findings emphasize the importance of tailored solutions for diverse passenger groups, as universal approaches prove inadequate. Methodologically, this paper employs a systematic literature review to synthesize insights and identify trends, focusing on AI applications in air-rail systems. Ethical and technical challenges, including data integration, algorithmic bias, and privacy concerns, are addressed, highlighting the need for robust governance mechanisms. The study advocates for advancements in joint ticketing, baggage handling, AI-driven personalized services, and global standards for multimodal transportation. The findings underscore the potential of AI to revolutionize air-rail networks, offering actionable insights for stakeholders to improve passenger experience and operational efficiency.