Aircraft taxiing conflict avoidance approach based on Gaussian spatial–temporal prediction

Abstract

To detect and avoid taxiing conflict on the airport surface and ensure the safety of airfield operation, constructing a Gaussian spatial–temporal prediction is very important. This paper summarizes the types of taxiing conflicts on the airport surface and the dynamic process of aircraft conflicts, and defines the taxiing conflict area based on the characteristics of aircraft types. Based on Gaussian spatial–temporal regression prediction and real-time taxiing speed, the taxiing conflict risk is quantified, and a dynamic interval taxiing speed feedback adjustment method is established. The proposed quantization method and feedback adjustment method are verified by simulation calculation and historical taxi data, respectively. Results show that the proposed method can quantitatively evaluate the aircraft conflict risk of cross-taxiing and dynamically adjust the taxiing speed of the aircraft through the conflict risk quantification value to control the aircraft conflict risk within a safe range and avoid taxiing conflicts.