Study On Dynamic Optimization Of Aircraft Taxiing Path

In recent years,China’s rapid economic development has led to the rapid growth of the civil aviation industry.However,this rapid growth has also brought unprecedented pressure on airport operations.Therefore,this thesis focuses on the optimization of aircraft taxiing paths on the airport surface,aiming to address issues such as high flight density,long taxiing time,and safety hazards.An optimization method based on dynamic programming is proposed to reduce taxiing time and improve operational efficiency.This method can be applied to address complex taxiing routes and potential conflict accidents during airport congestion,thereby optimizing airport operational efficiency and safety.The thesis begins by analyzing the connectivity of the airport surface network and abstracting the taxiway connections,constructing a topological graph of the airport surface taxiing structure using Changsha Airport as an example.Next,a modeling method based on intelligent agents is investigated,and in combination with the A* algorithm,an A* algorithmbased model is developed using the Any Logic simulation software.Basic aircraft taxiing information is obtained through field surveys and preprocessed to format the entry times of aircraft into the model time.The model is then used to plan and solve for the aircraft’s static taxiing paths.Subsequently,Python code is developed to create taxiing time windows for all aircraft,and using the code,conflict points and their occurrence times are determined through judgment and preprocessing.Following the principles of conflict detection and resolution,the conflict points are sequentially resolved,and the taxiing time windows of all affected aircraft are updated,resulting in optimized taxiing time windows.Finally,the thesis analyzes the rules of aircraft path and surface taxiing and uses the Any Logic simulation software to construct the airport surface taxiways.Based on the principles of aircraft taxiing,a logical flow of aircraft taxiing is established.The obtained static path information and dynamically optimized information are imported into the simulation model for validation,obtaining the taxiing time and distance for each aircraft.By comparing the results with real operational data from a peak period at Changsha Huanghua Airport,it is found that the dynamic optimization method based on dynamic programming can dynamically detect and resolve conflict points,facilitating aircraft diversion and effectively reducing taxiing time,flight delays,and improving airport operational efficiency.This validates the effectiveness of the proposed method.Compared to traditional static optimization methods,the dynamic optimization method presented in this thesis has significant advantages in reducing taxiing time and improving airport operational efficiency.In summary,this thesis provides an effective dynamic optimization method for airport taxiing scheduling problems.Through simulation experiments and data analysis,the validity of this method is verified.The research contributes to optimizing airport operations,reducing taxiing conflicts,and enhancing safety.