Optimizing and visualizing dynamic service performance for airspace users to enable safe and efficient urban air mobility in Dubai

Recent advancements in technology have broadened the capabilities of unmanned aerial vehicles (UAVs) in urban areas. However, the increase in UAV activities in low-altitude airspace brings substantial risks to people, structures, and other air traffic, necessitating regulated air traffic movements and thorough airspace information services for users. This study specifically aims to create and optimize an operational concept for managing UAV traffic in cities with high-rise buildings, focusing on Dubai in the United Arab Emirates. The concept includes UAV airspace design and operating heights and incorporates a grid system aligned with Dubai’s Road networks to avoid collisions. To maximize profitability and manage traffic load efficiently, two mathematical models are developed, and a genetic algorithm is proposed for solving large-scale instances. The concept’s efficacy in regulating UAV air traffic and its impact on service performance due to airspace constraints are validated through simulation using Dubai’s maps and building heights. This research, a collaboration involving international and national academic, industrial, and governmental entities, addresses the gap in research on UAV operations in densely populated urban areas and lays the foundation for further enhancements in UAV routing model