Aircraft Cross Taxiing Conflict Prediction and Avoidance Methods

With the rapid development of the civil aviation industry, the increasing number of flights has made ensuring the safety and efficiency of airport surface movements a pressing issue. This study establishes a mathematical model to predict the collision risk of aircraft in the intersection area in real time, and proposes appropriate intervention zones for avoidance, implementing a deceleration avoidance strategy. The model is validated using historical operational data from Beijing Capital International Airport, and the results indicate that the proposed model effectively reduces the collision probability to below 0.3. It demonstrates strong performance in predicting cross-path conflicts and reducing conflict risks. Additionally, the deceleration avoidance strategy further lowers the collision probability, improving both the safety and efficiency of airport surface operations. This research offers valuable insights for enhancing the operational efficiency and proactive safety levels of civil aviation airports.