Abstract:In order to address the threat to the safety of ground personnel and property after UAS failure, a risk assessment and route planning method for UAVs based on ballistic descent method is proposed. The descent characteristics and laws of UAV after failure are analyzed, the raster method is used to divide the airspace environment, and the risk assessment model of low-altitude airspace environment is constructed with different attributes on the ground. Combine the risk value, path length and airspace of the UAV flight, a multi-objective and multi-constrained UAV flight path planning model is established. Solving with improved ant colony algorithm: optimize the transfer probability to avoid ants falling into dead intervals and reduce blind search; improve the update of pheromone, adjust the adaptive coefficient to enhance the pheromone concentration of the optimal path, and improve the convergence speed and stability of the algorithm. Compared with the path planning of the traditional ant colony algorithm, the running time is shortened by 6.7%, the risk value of the optimal path is reduced by 41.45%, and the overall performance is improved by 18.0%.The simulation results show that the model and the improved algorithm can shorten the planning path generation time and ensure the economy of operation while improving the path safety.