Unmanned aerial vehicles (UAVs) are used in the rapidly expanding drone delivery market to carry packages and supplies to clients. Recently, the Central Economic Work Conference emphasized Platform economics, Low-altitude economics, and Automation combined logistic model. As logistics industry is the largest among the four main economic pillars in Hong Kong. Moreover, Hong Kong is a core city in GBA, having status as an international leader in sectors including innovation and technology. It is important to discover the possibility of low-altitude economics, hence we are going to suggest an approach to regulating flight and safety. We suggest supervised reinforcement learning for path planning and fly control. The environment combines information of geospatial data from the Hong Kong Land Department and weather data from the Hong Kong Observatory; The agent is the 6 degree-of-freedom of the drone; while the reward and action are related to legislative restrictions from civil aviation department, the delivery mission from the customer, risks from environment, and spatial occupied by other drones. The overall aim of this system is to regulate flight under complex urban environments, prevent accidents and crashes, avoid violation of law, and establish a manageable low-altitude aerospace.
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