Unmanned aerial vehicles (UAVs) are transforming modern transportation systems, with applications in last-mile delivery, urban air mobility (UAM), traffic monitoring, infrastructure inspection, and integration with intelligent transportation systems (ITS). This paper provides an overview of UAV technologies, describing various UAV configurations, alongside advancements in autonomous flight optimization, sense-and-avoid technology, real-time data transmission, and cooperative navigation. The integration of machine learning (ML) also enhances UAV capabilities, particularly in autonomous flight, collision avoidance, and data analytics, enabling efficient trajectory planning and adaptive response in dynamic environments. Case studies in transportation, infrastructure maintenance, and logistics demonstrate the practical impact and interdisciplinary nature of UAV applications. The paper also addresses cybersecurity challenges, proposing engineering strategies for system resilience. Furthermore, future directions emphasize potential integrations with ITS, smart grids, smart cities enabled by IoT, and sustainable materials, offering a comprehensive view of the transformative role of UAVs in transportation systems and underscoring the technological, ML-driven, logistical and regulatory considerations necessary for their broader adoption.



