Aviation Collision Risk Warning for Non-Tower Airport Based on Trajectory Prediction

With the development of the civil aviation industry, the throughput of airports continues to increase, including non-tower airports (small airports without the ability to actively communicate with aircraft). These non-tower civil airports can handle small aircraft such as personal aircraft well and lay a solid foundation for future automated aircraft. However, there is a high collision risk in taking off or landing because the probability of avoiding risks highly relies on the pilot’s flight proficiency and experience. To address this problem, we studied the collision risk of aircraft in non-tower airports and proposed a collision risk warning method based on trajectory prediction. The proposed method obtains the probability of future collisions by learning the flight patterns of all aircraft in non-tower airports, the impact of environmental wind speed on pilot behavior, and the interaction patterns between aircraft. At the same time, we conducted in-depth optimization of the probability integration calculation process under a conditional threshold to reduce the time complexity greatly. The simulation experiment results on non-tower airports show that the designed method for collision risk warning can effectively address the aircraft collision prediction problem in non-tower airports, and outperform other benchmark learning methods. It has significant guiding implications for improving airport intelligence and aircraft automation in the future.