A Risk-based UAS Traffic Network Model for Adaptive Urban Airspace Management

This paper presents a risk-based model for UAV path planning in urban low altitude environments.Firstly, the risks in urban environments were identified and classified into four groups, and the corresponding risk costs were categorized into five different levels.A general risk cost model was then developed for qualifying all related risk costs.Secondly, a ConOps for urban air route network with plane and cubical diagonals was built and the obtained risk cost information were ingested into the network to assist path planning.Finally, an A*cost algorithm was developed to generate a safe and cost-effective path for UAVs in urban low altitude airspace.Simulation results show that the novel route network structure with diagonals has better performance, with an average reduction of 17.56% for path distance.While the proposed A*cost algorithm has good results in terms of total cost and computational time, outperforming traditional Dijkstra and Ant Colony algorithm.