Low Altitude Airspace

Low-altitude airspace management focuses on safely and efficiently integrating increasing numbers of unmanned and autonomous aerial vehicles (UAVs) into existing airspace, particularly in urban environments. Current research emphasizes developing autonomous decision-making systems for UAVs and air traffic control, employing techniques like reinforcement learning, Monte Carlo tree search, and graph-based approaches to optimize path planning, conflict resolution, and airspace allocation. These advancements are crucial for enabling the safe and scalable deployment of urban air mobility and drone delivery services, while also addressing security concerns and improving overall airspace utilization.