An Analysis and Prediction Model of Aircraft Landing States on Wet Runways with Crosswind Based on Taxiing Dynamics Model

To address the frequent occurrence of runway excursion accidents in aviation safety, this study conducts a quantitative analysis of the factors influencing aircraft landing taxiing states and establishes a corresponding prediction model. A human-aircraft-environment coupled dynamics model for aircraft landing taxiing is developed in Simulink, focusing on the Airbus A320-214. This model incorporates a dynamic engine thrust module and integrates pilot operations, aircraft dynamics, crosswind, and wet runway surface conditions. Closed-loop simulations yield 3, 191 sets of data for analysis. The influence of various factors, such as water film thickness, pilot reaction speed, and touchdown ground speed, on runway excursions is quantified using multiple linear regression. The mechanism of thrust reverser imbalance affecting deviation distance is analyzed, leading to the establishment of predictive models for landing taxiing distance and deviation distance. The findings indicate that during landing taxiing, touchdown ground speed has a greater impact on taxiing distance than on deviation distance. Environmental factors like water film thickness, friction imbalance, and crosswind velocity are more likely to cause runway deviations. Among these, friction imbalance has the most pronounced effect on yaw direction, exceeding the impact of thrust reverser imbalance by a factor of 14.5, which ranks as the second most influential factor. Under specified conditions, a thrust reverser imbalance exceeding 0.4 pushes the deviation distance close to the safety threshold, representing a substantial risk. The multiple linear regression model for taxiing distance prediction demonstrates a coefficient of determination (R²) of 0.88, a mean absolute error (MAE) of 48.32 m, and a mean absolute percentage error (MAPE) of 7.75%. Prediction deviations for actual cases remain within 5%, indicating superior accuracy of the model for predicting aircraft landing taxiing distance.