This systematic literature review explores the integration of Autonomous Ground Vehicles (AGVs) into airport operations, focusing on key challenges, associated risks, and enabling technological innovations. The adoption of AGVs promises significant improvements in efficiency, safety, and sustainability across tasks such as baggage handling, aircraft towing, and runway maintenance. However, deploying AGVs in the dynamic, complex environments of airports presents significant obstacles, including challenges related to perception accuracy, sensor limitations, real-time decision-making, and cyber security risks. We applied the PRISMA methodology to screen 206 peer-reviewed articles from major databases, including Scopus, Web of Science, and PubMed. After screening, 14 studies were selected based on the inclusion criteria. The findings highlight the importance of advanced perception systems, multi-agent coordination, and Artificial Intelligence (AI)-based algorithms in enhancing AGVs performance. Furthermore, emerging innovations such as sensor fusion, transfer learning, and simulation-based development have proven effective in improving reliability and operational efficiency. This review contributes to current understanding of AGVs applications in airports and provides practical insights and recommendations for future research and development.
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